1D Convolution을 기본 구성 요소로 하는 EEG classifier를 학습해보는 노트북.
# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2
# Load some packages
import os
import glob
import json
from copy import deepcopy
import datetime
import matplotlib.pyplot as plt
import pprint
from IPython.display import clear_output
from tqdm.auto import tqdm
import numpy as np
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from torchvision import transforms
from typing import Type, Any, Callable, Union, List, Optional
# custom package
from utils.eeg_dataset import *
# Other settings
%matplotlib inline
%config InlineBackend.figure_format = 'retina' # cleaner text
plt.style.use('default')
# ['Solarize_Light2', '_classic_test_patch', 'bmh', 'classic', 'dark_background', 'fast',
# 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind',
# 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted',
# 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk',
# 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams["font.family"] = 'NanumGothic' # for Hangul in Windows
print('PyTorch version:', torch.__version__)
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
if torch.cuda.is_available(): print('cuda is available.')
else: print('cuda is unavailable.')
PyTorch version: 1.7.1 cuda is available.
# Data file path
root_path = r'dataset/02_Curated_Data/'
# Checkpoint
save_checkpoint = True
meta_path = os.path.join(root_path, 'metadata_debug.json')
with open(meta_path, 'r') as json_file:
metadata = json.load(json_file)
pprint.pprint(metadata[0])
{'age': 78,
'birth': '1940-06-02',
'dx1': 'mci_rf',
'edfname': '00001809_261018',
'events': [[0, 'Start Recording'],
[0, 'New Montage - Montage 002'],
[36396, 'Eyes Open'],
[72518, 'Eyes Closed'],
[73862, 'Eyes Open'],
[75248, 'Eyes Closed'],
[76728, 'swallowing'],
[77978, 'Eyes Open'],
[79406, 'Eyes Closed'],
[79996, 'Photic On - 3.0 Hz'],
[80288, 'Eyes Open'],
[81296, 'Eyes Closed'],
[82054, 'Photic Off'],
[84070, 'Photic On - 6.0 Hz'],
[84488, 'Eyes Open'],
[85538, 'Eyes Closed'],
[86086, 'Photic Off'],
[88144, 'Photic On - 9.0 Hz'],
[90160, 'Photic Off'],
[91458, 'Eyes Open'],
[92218, 'Photic On - 12.0 Hz'],
[92762, 'Eyes Closed'],
[94198, 'Photic Off'],
[94742, 'Eyes Open'],
[95708, 'Eyes Closed'],
[96256, 'Photic On - 15.0 Hz'],
[98272, 'Photic Off'],
[100330, 'Photic On - 18.0 Hz'],
[102346, 'Photic Off'],
[102596, 'Eyes Open'],
[103856, 'Eyes Closed'],
[104361, 'Photic On - 21.0 Hz'],
[106420, 'Photic Off'],
[106880, 'Eyes Open'],
[107804, 'Eyes Closed'],
[108435, 'Photic On - 24.0 Hz'],
[110452, 'Photic Off'],
[111080, 'Eyes Open'],
[112004, 'Eyes Closed'],
[112509, 'Photic On - 27.0 Hz'],
[114528, 'Photic Off'],
[114864, 'Eyes Open'],
[116124, 'Eyes Closed'],
[116544, 'Photic On - 30.0 Hz'],
[118602, 'Photic Off'],
[126672, 'artifact'],
[134030, 'Move'],
[135584, 'Eyes Open'],
[136668, 'Eyes Closed'],
[139818, 'Eyes Open'],
[141414, 'Eyes Closed'],
[145000, 'Paused']],
'label': ['mci', 'mci_amnestic', 'mci_amnestic_rf'],
'record': '2018-10-26T15:46:26',
'serial': '00001'}
diagnosis_filter = [
# Normal
{'type': 'Normal',
'include': ['normal'],
'exclude': []},
# Non-vascular MCI
{'type': 'MCI or Dementia',
'include': ['mci', 'dementia'],
'exclude': ['mci_vascular', 'vd']},
]
def generate_class_label(label):
for c, f in enumerate(diagnosis_filter):
# inc = set(f['include']) & set(label) == set(f['include'])
inc = len(set(f['include']) & set(label)) > 0
exc = len(set(f['exclude']) & set(label)) == 0
if inc and exc:
return (c, f['type'])
return (-1, 'The others')
class_label_to_type = [d_f['type'] for d_f in diagnosis_filter]
print('class_label_to_type:', class_label_to_type)
class_label_to_type: ['Normal', 'MCI or Dementia']
splitted_metadata = [[] for i in diagnosis_filter]
for m in metadata:
c, n = generate_class_label(m['label'])
if c >= 0:
m['class_type'] = n
m['class_label'] = c
splitted_metadata[c].append(m)
for i, split in enumerate(splitted_metadata):
if len(split) == 0:
print(f'(Warning) Split group {i} has no data.')
else:
print(f'- There are {len(split):} data belonging to {split[0]["class_type"]}')
- There are 463 data belonging to Normal - There are 576 data belonging to MCI or Dementia
# random seed
random.seed(0)
# Train : Val : Test = 8 : 1 : 1
ratio1 = 0.8
ratio2 = 0.1
metadata_train = []
metadata_val = []
metadata_test = []
for split in splitted_metadata:
random.shuffle(split)
n1 = round(len(split) * ratio1)
n2 = n1 + round(len(split) * ratio2)
metadata_train.extend(split[:n1])
metadata_val.extend(split[n1:n2])
metadata_test.extend(split[n2:])
random.shuffle(metadata_train)
random.shuffle(metadata_val)
random.shuffle(metadata_test)
print('Train data size\t\t:', len(metadata_train))
print('Validation data size\t:', len(metadata_val))
print('Test data size\t\t:', len(metadata_test))
print('\n', '--- Recheck ---', '\n')
train_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_train:
train_class_nums[m['class_label']] += 1
val_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_val:
val_class_nums[m['class_label']] += 1
test_class_nums = np.zeros((len(class_label_to_type)), dtype=np.int32)
for m in metadata_test:
test_class_nums[m['class_label']] += 1
print('Train data label distribution\t:', train_class_nums, train_class_nums.sum())
print('Val data label distribution\t:', val_class_nums, val_class_nums.sum())
print('Test data label distribution\t:', test_class_nums, test_class_nums.sum())
# random seed
random.seed()
# print([m['serial'] for m in metadata_train[:15]])
# print([m['serial'] for m in metadata_val[:15]])
# print([m['serial'] for m in metadata_test[:15]])
Train data size : 831 Validation data size : 104 Test data size : 104 --- Recheck --- Train data label distribution : [370 461] 831 Val data label distribution : [46 58] 104 Test data label distribution : [47 57] 104
ages = []
for m in metadata_train:
ages.append(m['age'])
ages = np.array(ages)
age_mean = np.mean(ages)
age_std = np.std(ages)
print('Age mean and standard deviation:')
print(age_mean, age_std)
Age mean and standard deviation: 70.1841155234657 9.744314293002148
composed = transforms.Compose([EEGNormalizeAge(mean=age_mean, std=age_std),
EEGDropPhoticChannel(),
EEGRandomCrop(crop_length=200*10), # 10 sec
EEGNormalizePerSignal(),
EEGToTensor()])
train_dataset = EEGDataset(root_path, metadata_train, composed)
val_dataset = EEGDataset(root_path, metadata_val, composed)
test_dataset = EEGDataset(root_path, metadata_test, composed)
print(train_dataset[0]['signal'].shape)
print(train_dataset[0])
print()
print('-' * 100)
print()
print(val_dataset[0]['signal'].shape)
print(val_dataset[0])
print()
print('-' * 100)
print()
print(test_dataset[0]['signal'].shape)
print(test_dataset[0])
torch.Size([20, 2000])
{'signal': tensor([[ 0.0694, 0.0270, 0.0058, ..., 1.4060, 1.3529, 1.3317],
[-0.3927, -0.3927, -0.4289, ..., 0.8747, 0.9109, 0.8023],
[ 0.3382, 0.4732, 0.4732, ..., 0.3382, 0.4057, 0.2707],
...,
[ 1.2471, 1.3595, 1.2471, ..., 1.1348, 1.1348, 1.2471],
[-0.7964, -0.6749, -0.6749, ..., -0.1888, -0.0673, 0.0543],
[-0.1000, -0.1072, -0.1216, ..., -0.3376, -0.2656, -0.3016]]), 'age': tensor(-1.2504), 'class_label': tensor(0), 'metadata': {'serial': '01012', 'edfname': '01212635_270515', 'birth': '1956-06-01', 'record': '2015-05-27T09:37:24', 'age': 58, 'dx1': 'cb_normal', 'label': ['normal', 'cb_normal'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [400, 'Eyes Open'], [7918, 'Eyes Closed'], [14091, 'Eyes Open'], [18208, 'Eyes Closed'], [24256, 'Eyes Open'], [30724, 'Eyes Closed'], [36562, 'Eyes Open'], [42190, 'Eyes Closed'], [48910, 'Eyes Open'], [55126, 'Eyes Closed'], [60417, 'Eyes Open'], [66004, 'Eyes Closed'], [71968, 'Eyes Open'], [78310, 'Eyes Closed'], [84442, 'Eyes Open'], [90070, 'Eyes Closed'], [96076, 'Eyes Open'], [102082, 'Eyes Closed'], [108844, 'Eyes Open'], [113674, 'Eyes Closed'], [120000, 'Paused']], 'class_type': 'Normal', 'class_label': 0}}
----------------------------------------------------------------------------------------------------
torch.Size([20, 2000])
{'signal': tensor([[ 0.5622, 1.4436, 1.3758, ..., -0.2514, -0.3531, -0.4887],
[ 0.2699, -0.1923, 0.2699, ..., -0.4696, -0.4696, -0.0999],
[ 0.3250, -0.1590, 0.1636, ..., -0.1590, -0.3203, 0.1636],
...,
[-0.4070, -0.9008, -0.7362, ..., 0.5805, -0.0779, -0.2424],
[-1.8172, -2.0563, -1.8172, ..., 0.2148, -0.9805, -2.0563],
[ 0.2051, 0.1626, 0.0882, ..., -0.8894, -0.8682, -0.8363]]), 'age': tensor(-0.0189), 'class_label': tensor(1), 'metadata': {'serial': '00389', 'edfname': '00727364_231118', 'birth': '1948-09-16', 'record': '2018-11-23T16:23:15', 'age': 70, 'dx1': 'mci amnestic', 'label': ['mci', 'mci_amnestic'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 002'], [36234, 'Eyes Open'], [48986, 'artifact'], [72192, 'Eyes Closed'], [73998, 'Eyes Open'], [75216, 'Eyes Closed'], [76166, 'Eyes Open'], [77396, 'Eyes Closed'], [78244, 'Photic On - 3.0 Hz'], [78620, 'Eyes Open'], [79334, 'Eyes Closed'], [80260, 'Photic Off'], [82276, 'Photic On - 6.0 Hz'], [82652, 'Eyes Open'], [83786, 'Eyes Closed'], [84292, 'Photic Off'], [86350, 'Photic On - 9.0 Hz'], [88366, 'Photic Off'], [88658, 'Eyes Open'], [89792, 'Eyes Closed'], [90424, 'Photic On - 12.0 Hz'], [92440, 'Photic Off'], [94456, 'Photic On - 15.0 Hz'], [96484, 'Photic Off'], [96902, 'Eyes Open'], [97868, 'Eyes Closed'], [98542, 'Photic On - 18.0 Hz'], [100558, 'Photic Off'], [102574, 'Photic On - 21.0 Hz'], [104632, 'Photic Off'], [105302, 'Eyes Open'], [106309, 'Eyes Closed'], [106648, 'Photic On - 24.0 Hz'], [108664, 'Photic Off'], [110008, 'cough'], [110724, 'Photic On - 27.0 Hz'], [112744, 'Photic Off'], [114759, 'Photic On - 30.0 Hz'], [116818, 'Photic Off'], [117846, 'A2 check'], [118000, 'Paused'], [120000, 'Recording Resumed'], [148064, 'Eyes Open'], [148562, 'swallowing'], [149492, 'Eyes Closed'], [158200, 'Paused']], 'class_type': 'MCI or Dementia', 'class_label': 1}}
----------------------------------------------------------------------------------------------------
torch.Size([20, 2000])
{'signal': tensor([[ 0.2817, 0.3468, 0.4770, ..., 0.8999, 0.9325, 0.9650],
[-0.5928, -0.4570, -0.3212, ..., -0.4570, -0.1854, 0.0862],
[-0.3624, -0.1561, -0.1561, ..., -0.1561, 0.0501, -0.1561],
...,
[-0.8221, -0.8221, -0.8221, ..., -0.3785, -0.1567, -0.1567],
[-0.0113, -0.1615, -0.3116, ..., -0.3116, -0.4618, -0.6120],
[-1.6052, -1.4395, -1.4244, ..., 0.6215, 0.4915, 0.3427]]), 'age': tensor(1.0073), 'class_label': tensor(0), 'metadata': {'serial': '00299', 'edfname': '00671212_160819', 'birth': '1938-08-17', 'record': '2019-08-16T10:57:03', 'age': 80, 'dx1': 'smi', 'label': ['normal', 'smi'], 'events': [[0, 'Start Recording'], [0, 'New Montage - Montage 005'], [1773, 'Eyes Closed'], [6000, 'Cz check'], [7612, 'Eyes Open'], [12912, 'Eyes Closed'], [18078, 'Eyes Open'], [23958, 'Eyes Closed'], [29288, 'Eyes Open'], [35934, 'Eyes Closed'], [41856, 'Eyes Open'], [47862, 'Eyes Closed'], [54460, 'Eyes Open'], [59962, 'Eyes Closed'], [66178, 'Eyes Open'], [71008, 'Eyes Closed'], [73948, 'Photic On - 3.0 Hz'], [74158, 'Eyes Open'], [75166, 'Eyes Closed'], [75964, 'Photic Off'], [77980, 'Photic On - 6.0 Hz'], [78358, 'Eyes Open'], [79282, 'Eyes Closed'], [80038, 'Photic Off'], [82054, 'Photic On - 9.0 Hz'], [84070, 'Photic Off'], [86128, 'Photic On - 12.0 Hz'], [87640, 'Eyes Open'], [88144, 'Photic Off'], [88396, 'Eyes Closed'], [90202, 'Photic On - 15.0 Hz'], [92218, 'Photic Off'], [92722, 'Eyes Open'], [93772, 'Eyes Closed'], [94234, 'Photic On - 18.0 Hz'], [96250, 'Photic Off'], [98308, 'Photic On - 21.0 Hz'], [100324, 'Photic Off'], [102382, 'Photic On - 24.0 Hz'], [104398, 'Photic Off'], [106414, 'Photic On - 27.0 Hz'], [108430, 'Photic Off'], [110488, 'Photic On - 30.0 Hz'], [111580, 'Eyes Open'], [111790, 'Photic Off'], [112420, 'Eyes Closed'], [113200, 'Paused']], 'class_type': 'Normal', 'class_label': 0}}
print('Current PyTorch device:', device)
if device.type == 'cuda':
num_workers = 0 # A number other than 0 causes an error
pin_memory = True
else:
num_workers = 0
pin_memory = False
train_loader = DataLoader(train_dataset,
batch_size=32,
shuffle=True,
drop_last=True,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
for i_batch, sample_batched in enumerate(train_loader):
sample_batched['signal'].to(device)
sample_batched['age'].to(device)
sample_batched['class_label'].to(device)
print(i_batch,
sample_batched['signal'].shape,
sample_batched['age'].shape,
sample_batched['class_label'].shape,
len(sample_batched['metadata']))
if i_batch > 3:
break
Current PyTorch device: cuda 0 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 1 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 2 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 3 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32 4 torch.Size([32, 20, 2000]) torch.Size([32]) torch.Size([32]) 32
train_loader = DataLoader(train_dataset,
batch_size=32,
shuffle=True,
drop_last=True,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
val_loader = DataLoader(val_dataset,
batch_size=32,
shuffle=False,
drop_last=False,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
test_loader = DataLoader(test_dataset,
batch_size=32,
shuffle=False,
drop_last=False,
num_workers=num_workers,
pin_memory=pin_memory,
collate_fn=eeg_collate_fn)
from torch.utils.tensorboard import SummaryWriter
import ipynbname
nb_fname = ipynbname.name()
def count_parameters(model):
return sum(p.numel() for p in model.parameters() if p.requires_grad)
def visualize_network_tensorboard(model, name):
# default `log_dir` is "runs" - we'll be more specific here
writer = SummaryWriter('runs/' + nb_fname + '_' + name)
for batch_i, sample_batched in enumerate(train_loader):
# pull up the batch data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
writer.add_graph(model, (x, age))
output = model(x, age, print_shape=True)
break
writer.close()
def train_one_epoch(model, optimizer, log_interval):
# turn the models to training mode
model.train()
losses = []
correct, total = (0, 0)
C = len(class_label_to_type)
train_confusion = np.zeros((C, C), dtype=np.int32)
for batch_i, sample_batched in enumerate(train_loader):
# pull up the batch data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
# negative log-likelihood for a tensor of size (batch x n_output)
pred = F.log_softmax(output, dim=1)
loss = F.nll_loss(pred, target)
# backprop and update
loss.backward()
optimizer.step()
optimizer.zero_grad()
# record loss
losses.append(loss.item())
# train accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
train_confusion += calculate_confusion_matrix(pred, target)
# print training stats
if log_interval is not None and (batch_i + 1) % log_interval == 0:
print(f'- Iter {batch_i + 1:03d} / {len(train_loader):03d}, Loss: {loss.item():.06f}')
train_accuracy = 100.0 * correct / total
return (losses, train_accuracy, train_confusion)
def check_val_accuracy(model, repeat=1):
model.eval()
correct, total = (0, 0)
C = len(class_label_to_type)
val_confusion = np.zeros((C, C), dtype=np.int32)
for k in range(repeat):
for sample_batched in val_loader:
# pull up the data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
pred = F.log_softmax(output, dim=1)
# val accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
val_confusion += calculate_confusion_matrix(pred, target)
val_accuracy = 100.0 * correct / total
return (val_accuracy, val_confusion)
def check_test_accuracy(model, repeat=1):
model.eval()
correct, total = (0, 0)
C = len(class_label_to_type)
test_confusion = np.zeros((C, C), dtype=np.int32)
test_debug = {data['metadata']['serial']:
{'GT': data['class_label'].item(),
'Acc': 0,
'Pred': [0] * C} for data in test_dataset}
for k in range(repeat):
for sample_batched in test_loader:
# pull up the data
x = sample_batched['signal'].to(device)
age = sample_batched['age'].to(device)
target = sample_batched['class_label'].to(device)
# apply model on whole batch directly on device
output = model(x, age)
pred = F.log_softmax(output, dim=1)
# test accuracy
pred = pred.argmax(dim=-1)
correct += pred.squeeze().eq(target).sum().item()
total += pred.shape[0]
# confusion matrix
test_confusion += calculate_confusion_matrix(pred, target)
# test debug
for n in range(pred.shape[0]):
serial = sample_batched['metadata'][n]['serial']
test_debug[serial]['edfname'] = sample_batched['metadata'][n]['edfname']
test_debug[serial]['Pred'][pred[n].item()] += 1
acc = test_debug[serial]['Pred'][target[n].item()] / np.sum(test_debug[serial]['Pred']) * 100
test_debug[serial]['Acc'] = f'{acc:>6.02f}%'
test_accuracy = 100.0 * correct / total
return (test_accuracy, test_confusion, test_debug)
def calculate_confusion_matrix(pred, target):
N = target.shape[0]
C = len(class_label_to_type)
confusion = np.zeros((C, C), dtype=np.int32)
for i in range(N):
r = target[i]
c = pred[i]
confusion[r, c] += 1
return confusion
def draw_loss_plot(loss_history):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.plot(loss_history)
ax.vlines(0, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)
for e in range(1, n_epoch + 1):
if e % lr_schedule_step == 0:
ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='m', alpha=0.3)
else:
ax.vlines(e*len(train_loader) - 1, 0, 1, transform=ax.get_xaxis_transform(), colors='k', alpha=0.1)
ax.set_title('Loss Plot')
ax.set_xlabel('Iteration')
ax.set_ylabel('Training Loss')
plt.show()
fig.clear()
plt.close(fig)
def draw_accuracy_history(train_acc_history, val_acc_history):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(15.0, 6.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.plot(train_acc_history, 'r-', label='Train accuracy')
ax.plot(val_acc_history, 'b-', label='Validation accuracy')
ax.legend(loc='lower right')
ax.set_title('Accuracy Plot during Training')
ax.set_xlabel('Epoch')
ax.set_ylabel('Accuracy (%)')
plt.show()
fig.clear()
plt.close(fig)
def draw_confusion(confusion):
C = len(class_label_to_type)
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
plt.rcParams['image.cmap'] = 'jet' # 'nipy_spectral'
fig = plt.figure(num=1, clear=True, figsize=(5.0, 5.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
im = ax.imshow(confusion, alpha=0.8)
ax.set_xticks(np.arange(C))
ax.set_yticks(np.arange(C))
ax.set_xticklabels(class_label_to_type)
ax.set_yticklabels(class_label_to_type)
for r in range(C):
for c in range(C):
text = ax.text(c, r, confusion[r, c],
ha="center", va="center", color='k')
ax.set_title('Confusion Matrix')
ax.set_xlabel('Prediction')
ax.set_ylabel('Ground Truth')
plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
plt.show()
fig.clear()
plt.close(fig)
def learning_rate_search(model, min_log_lr, max_log_lr, trials, epochs):
learning_rate_record = []
for t in tqdm(range(trials)):
log_lr = np.random.uniform(min_log_lr, max_log_lr)
lr = 10 ** log_lr
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=lr, weight_decay=0.0001)
for e in range(epochs):
_, train_accuracy, _ = train_one_epoch(model, optimizer, log_interval=None)
# Train accuracy for the final epoch is stored
learning_rate_record.append((log_lr, train_accuracy))
return learning_rate_record
def draw_learning_rate_record(learning_rate_record):
plt.style.use('default') # default, ggplot, fivethirtyeight, classic
fig = plt.figure(num=1, clear=True, figsize=(8.0, 8.0), constrained_layout=True)
ax = fig.add_subplot(1, 1, 1)
ax.set_title('Learning Rate Search')
ax.set_xlabel('Learning rate in log-scale')
ax.set_ylabel('Train accuracy')
for log_lr, val_accuracy in learning_rate_record:
ax.scatter(log_lr, val_accuracy, c='r',
alpha=0.5, edgecolors='none')
plt.show()
fig.clear()
plt.close(fig)
class TinyNet(nn.Module):
def __init__(self, n_input=20, n_output=3, stride=7, n_channel=64,
use_age=True, final_pool='average'):
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.use_age = use_age
self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=35, stride=stride)
self.bn1 = nn.BatchNorm1d(n_channel)
self.pool1 = nn.MaxPool1d(4)
self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=7)
self.bn2 = nn.BatchNorm1d(n_channel)
self.pool2 = nn.MaxPool1d(2)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
if self.use_age:
self.fc1 = nn.Linear(n_channel + 1, n_channel)
else:
self.fc1 = nn.Linear(n_channel, n_channel)
self.dropout = nn.Dropout(p=0.3)
self.bnfc1 = nn.BatchNorm1d(n_channel)
self.fc2 = nn.Linear(n_channel, n_output)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def forward(self, x, age, print_shape=False):
# conv-bn-relu-pool
x = self.conv1(x)
x = F.relu(self.bn1(x))
x = self.pool1(x)
x = self.conv2(x)
x = F.relu(self.bn2(x))
x = self.pool2(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
# fc-bn-dropout-relu-fc
x = self.fc1(x)
x = self.bnfc1(x)
x = self.dropout(x)
x = F.relu(x)
x = self.fc2(x)
return x
# return F.log_softmax(x, dim=1)
model = TinyNet(n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'TinyNet')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
TinyNet( (conv1): Conv1d(20, 64, kernel_size=(35,), stride=(7,)) (bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool1): MaxPool1d(kernel_size=4, stride=4, padding=0, dilation=1, ceil_mode=False) (conv2): Conv1d(64, 64, kernel_size=(7,), stride=(1,)) (bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (final_pool): AdaptiveMaxPool1d(output_size=1) (fc1): Linear(in_features=65, out_features=64, bias=True) (dropout): Dropout(p=0.3, inplace=False) (bnfc1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (fc2): Linear(in_features=64, out_features=2, bias=True) ) Shape right before squeezing: torch.Size([32, 64, 32]) The Number of parameters of the model: 78,338
# record = learning_rate_search(model,
# min_log_lr=-4.5,
# max_log_lr=-1.4,
# trials=300,
# epochs=1)
# draw_learning_rate_record(record)
# best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
best_log_lr = -2.0
print('best_log_lr:', best_log_lr)
best_log_lr: -2.0
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.635307 - Iter 024 / 025, Loss: 0.545660 * Train accuracy / confusion: 60.88% / [[166, 184], [129, 321]], * Val accuracy / confusion: 56.35% / [[5, 225], [2, 288]] ------------------------------ Epoch 002 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.598025 - Iter 024 / 025, Loss: 0.625390 * Train accuracy / confusion: 63.88% / [[193, 159], [130, 318]], * Val accuracy / confusion: 64.81% / [[185, 45], [138, 152]] ------------------------------ Epoch 003 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.615729 - Iter 024 / 025, Loss: 0.446697 * Train accuracy / confusion: 67.00% / [[188, 163], [101, 348]], * Val accuracy / confusion: 65.77% / [[74, 156], [22, 268]] ------------------------------ Epoch 004 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.499934 - Iter 024 / 025, Loss: 0.395270 * Train accuracy / confusion: 66.88% / [[206, 151], [114, 329]], * Val accuracy / confusion: 64.23% / [[62, 168], [18, 272]] ------------------------------ Epoch 005 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.770893 - Iter 024 / 025, Loss: 0.595334 * Train accuracy / confusion: 66.50% / [[192, 161], [107, 340]], * Val accuracy / confusion: 72.12% / [[153, 77], [68, 222]] ------------------------------ Epoch 006 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.656105 - Iter 024 / 025, Loss: 0.523004 * Train accuracy / confusion: 69.00% / [[217, 141], [107, 335]], * Val accuracy / confusion: 72.69% / [[159, 71], [71, 219]] ------------------------------ Epoch 007 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.645615 - Iter 024 / 025, Loss: 0.386769 * Train accuracy / confusion: 70.62% / [[232, 125], [110, 333]], * Val accuracy / confusion: 70.58% / [[117, 113], [40, 250]] ------------------------------ Epoch 008 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.587221 - Iter 024 / 025, Loss: 0.495223 * Train accuracy / confusion: 68.88% / [[219, 137], [112, 332]], * Val accuracy / confusion: 71.92% / [[171, 59], [87, 203]] ------------------------------ Epoch 009 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.675945 - Iter 024 / 025, Loss: 0.561914 * Train accuracy / confusion: 71.12% / [[236, 116], [115, 333]], * Val accuracy / confusion: 73.46% / [[145, 85], [53, 237]] ------------------------------ Epoch 010 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.638837 - Iter 024 / 025, Loss: 0.601490 * Train accuracy / confusion: 71.00% / [[227, 125], [107, 341]], * Val accuracy / confusion: 68.85% / [[95, 135], [27, 263]] ------------------------------ Epoch 011 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.538973 - Iter 024 / 025, Loss: 0.560006 * Train accuracy / confusion: 72.00% / [[219, 140], [84, 357]], * Val accuracy / confusion: 71.73% / [[170, 60], [87, 203]] ------------------------------ Epoch 012 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.475916 - Iter 024 / 025, Loss: 0.668958 * Train accuracy / confusion: 70.50% / [[231, 124], [112, 333]], * Val accuracy / confusion: 75.00% / [[160, 70], [60, 230]] ------------------------------ Epoch 013 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.405778 - Iter 024 / 025, Loss: 0.522562 * Train accuracy / confusion: 72.38% / [[209, 144], [77, 370]], * Val accuracy / confusion: 72.69% / [[154, 76], [66, 224]] ------------------------------ Epoch 014 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.490699 - Iter 024 / 025, Loss: 0.620355 * Train accuracy / confusion: 72.00% / [[217, 139], [85, 359]], * Val accuracy / confusion: 72.12% / [[155, 75], [70, 220]] ------------------------------ Epoch 015 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.580284 - Iter 024 / 025, Loss: 0.483805 * Train accuracy / confusion: 71.12% / [[226, 130], [101, 343]], * Val accuracy / confusion: 70.19% / [[102, 128], [27, 263]] ------------------------------ Epoch 016 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.530572 - Iter 024 / 025, Loss: 0.504406 * Train accuracy / confusion: 71.75% / [[227, 131], [95, 347]], * Val accuracy / confusion: 71.73% / [[128, 102], [45, 245]] ------------------------------ Epoch 017 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.442891 - Iter 024 / 025, Loss: 0.778906 * Train accuracy / confusion: 71.62% / [[218, 138], [89, 355]], * Val accuracy / confusion: 68.08% / [[116, 114], [52, 238]] ------------------------------ Epoch 018 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.511452 - Iter 024 / 025, Loss: 0.537335 * Train accuracy / confusion: 73.62% / [[236, 119], [92, 353]], * Val accuracy / confusion: 67.50% / [[106, 124], [45, 245]] ------------------------------ Epoch 019 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.491126 - Iter 024 / 025, Loss: 0.428570 * Train accuracy / confusion: 74.75% / [[244, 113], [89, 354]], * Val accuracy / confusion: 74.04% / [[159, 71], [64, 226]] ------------------------------ Epoch 020 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.585395 - Iter 024 / 025, Loss: 0.571922 * Train accuracy / confusion: 72.12% / [[225, 133], [90, 352]], * Val accuracy / confusion: 72.12% / [[128, 102], [43, 247]] ------------------------------ Epoch 021 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.522491 - Iter 024 / 025, Loss: 0.461649 * Train accuracy / confusion: 71.75% / [[229, 123], [103, 345]], * Val accuracy / confusion: 71.92% / [[140, 90], [56, 234]] ------------------------------ Epoch 022 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.492028 - Iter 024 / 025, Loss: 0.626595 * Train accuracy / confusion: 71.12% / [[213, 143], [88, 356]], * Val accuracy / confusion: 71.92% / [[116, 114], [32, 258]] ------------------------------ Epoch 023 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.588632 - Iter 024 / 025, Loss: 0.634321 * Train accuracy / confusion: 72.38% / [[229, 127], [94, 350]], * Val accuracy / confusion: 72.31% / [[123, 107], [37, 253]] ------------------------------ Epoch 024 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.555048 - Iter 024 / 025, Loss: 0.585375 * Train accuracy / confusion: 73.00% / [[221, 133], [83, 363]], * Val accuracy / confusion: 72.50% / [[142, 88], [55, 235]] ------------------------------ Epoch 025 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.502240 - Iter 024 / 025, Loss: 0.608486 * Train accuracy / confusion: 74.88% / [[235, 124], [77, 364]], * Val accuracy / confusion: 71.92% / [[137, 93], [53, 237]] ------------------------------ Epoch 026 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.505636 - Iter 024 / 025, Loss: 0.604604 * Train accuracy / confusion: 72.12% / [[218, 138], [85, 359]], * Val accuracy / confusion: 72.88% / [[141, 89], [52, 238]] ------------------------------ Epoch 027 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.532757 - Iter 024 / 025, Loss: 0.655379 * Train accuracy / confusion: 73.75% / [[223, 131], [79, 367]], * Val accuracy / confusion: 72.69% / [[143, 87], [55, 235]] ------------------------------ Epoch 028 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.542824 - Iter 024 / 025, Loss: 0.419367 * Train accuracy / confusion: 74.12% / [[231, 124], [83, 362]], * Val accuracy / confusion: 69.04% / [[93, 137], [24, 266]] ------------------------------ Epoch 029 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.616473 - Iter 024 / 025, Loss: 0.689271 * Train accuracy / confusion: 71.12% / [[230, 127], [104, 339]], * Val accuracy / confusion: 73.85% / [[156, 74], [62, 228]] ------------------------------ Epoch 030 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.429878 - Iter 024 / 025, Loss: 0.553707 * Train accuracy / confusion: 73.50% / [[236, 121], [91, 352]], * Val accuracy / confusion: 73.85% / [[180, 50], [86, 204]] ------------------------------ Epoch 031 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.468223 - Iter 024 / 025, Loss: 0.384459 * Train accuracy / confusion: 74.38% / [[252, 105], [100, 343]], * Val accuracy / confusion: 70.38% / [[172, 58], [96, 194]] ------------------------------ Epoch 032 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.539315 - Iter 024 / 025, Loss: 0.599091 * Train accuracy / confusion: 72.00% / [[230, 129], [95, 346]], * Val accuracy / confusion: 74.04% / [[164, 66], [69, 221]] ------------------------------ Epoch 033 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.565916 - Iter 024 / 025, Loss: 0.516768 * Train accuracy / confusion: 73.00% / [[244, 115], [101, 340]], * Val accuracy / confusion: 70.96% / [[113, 117], [34, 256]] ------------------------------ Epoch 034 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.630812 - Iter 024 / 025, Loss: 0.502057 * Train accuracy / confusion: 72.50% / [[223, 135], [85, 357]], * Val accuracy / confusion: 75.38% / [[153, 77], [51, 239]] ------------------------------ Epoch 035 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.552600 - Iter 024 / 025, Loss: 0.463752 * Train accuracy / confusion: 75.62% / [[236, 122], [73, 369]], * Val accuracy / confusion: 72.12% / [[105, 125], [20, 270]] ------------------------------ Epoch 036 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.536434 - Iter 024 / 025, Loss: 0.538284 * Train accuracy / confusion: 74.25% / [[225, 129], [77, 369]], * Val accuracy / confusion: 74.62% / [[152, 78], [54, 236]] ------------------------------ Epoch 037 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.417588 - Iter 024 / 025, Loss: 0.681722 * Train accuracy / confusion: 73.62% / [[237, 118], [93, 352]], * Val accuracy / confusion: 75.77% / [[144, 86], [40, 250]] ------------------------------ Epoch 038 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.666140 - Iter 024 / 025, Loss: 0.435170 * Train accuracy / confusion: 72.00% / [[216, 144], [80, 360]], * Val accuracy / confusion: 72.12% / [[118, 112], [33, 257]] ------------------------------ Epoch 039 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.531104 - Iter 024 / 025, Loss: 0.611874 * Train accuracy / confusion: 74.50% / [[236, 121], [83, 360]], * Val accuracy / confusion: 67.31% / [[88, 142], [28, 262]] ------------------------------ Epoch 040 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.522652 - Iter 024 / 025, Loss: 0.665120 * Train accuracy / confusion: 73.88% / [[248, 111], [98, 343]], * Val accuracy / confusion: 70.00% / [[126, 104], [52, 238]] ------------------------------ Epoch 041 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.572764 - Iter 024 / 025, Loss: 0.515827 * Train accuracy / confusion: 72.50% / [[215, 137], [83, 365]], * Val accuracy / confusion: 74.23% / [[161, 69], [65, 225]] ------------------------------ Epoch 042 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.486671 - Iter 024 / 025, Loss: 0.541009 * Train accuracy / confusion: 73.50% / [[227, 133], [79, 361]], * Val accuracy / confusion: 72.69% / [[156, 74], [68, 222]] ------------------------------ Epoch 043 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.520194 - Iter 024 / 025, Loss: 0.547590 * Train accuracy / confusion: 74.12% / [[242, 115], [92, 351]], * Val accuracy / confusion: 75.38% / [[153, 77], [51, 239]] ------------------------------ Epoch 044 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.587530 - Iter 024 / 025, Loss: 0.431146 * Train accuracy / confusion: 75.62% / [[238, 116], [79, 367]], * Val accuracy / confusion: 74.42% / [[150, 80], [53, 237]] ------------------------------ Epoch 045 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.545340 - Iter 024 / 025, Loss: 0.558361 * Train accuracy / confusion: 71.25% / [[219, 135], [95, 351]], * Val accuracy / confusion: 74.62% / [[147, 83], [49, 241]] ------------------------------ Epoch 046 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.562736 - Iter 024 / 025, Loss: 0.593282 * Train accuracy / confusion: 72.88% / [[228, 130], [87, 355]], * Val accuracy / confusion: 73.85% / [[140, 90], [46, 244]] ------------------------------ Epoch 047 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.624452 - Iter 024 / 025, Loss: 0.546690 * Train accuracy / confusion: 73.25% / [[226, 128], [86, 360]], * Val accuracy / confusion: 71.92% / [[158, 72], [74, 216]] ------------------------------ Epoch 048 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.457758 - Iter 024 / 025, Loss: 0.528866 * Train accuracy / confusion: 73.25% / [[220, 131], [83, 366]], * Val accuracy / confusion: 71.35% / [[134, 96], [53, 237]] ------------------------------ Epoch 049 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.473740 - Iter 024 / 025, Loss: 0.526016 * Train accuracy / confusion: 72.88% / [[209, 146], [71, 374]], * Val accuracy / confusion: 72.50% / [[132, 98], [45, 245]] ------------------------------ Epoch 050 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.547450 - Iter 024 / 025, Loss: 0.580080 * Train accuracy / confusion: 73.62% / [[254, 106], [105, 335]], * Val accuracy / confusion: 73.08% / [[152, 78], [62, 228]] ------------------------------ Epoch 051 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.443803 - Iter 024 / 025, Loss: 0.528295 * Train accuracy / confusion: 73.50% / [[217, 136], [76, 371]], * Val accuracy / confusion: 73.27% / [[138, 92], [47, 243]] ------------------------------ Epoch 052 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.605649 - Iter 024 / 025, Loss: 0.526169 * Train accuracy / confusion: 74.00% / [[252, 103], [105, 340]], * Val accuracy / confusion: 74.81% / [[154, 76], [55, 235]] ------------------------------ Epoch 053 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.731795 - Iter 024 / 025, Loss: 0.563490 * Train accuracy / confusion: 74.88% / [[224, 131], [70, 375]], * Val accuracy / confusion: 71.15% / [[181, 49], [101, 189]] ------------------------------ Epoch 054 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.416832 - Iter 024 / 025, Loss: 0.740131 * Train accuracy / confusion: 73.00% / [[238, 122], [94, 346]], * Val accuracy / confusion: 73.08% / [[142, 88], [52, 238]] ------------------------------ Epoch 055 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.430323 - Iter 024 / 025, Loss: 0.458606 * Train accuracy / confusion: 76.38% / [[244, 112], [77, 367]], * Val accuracy / confusion: 71.54% / [[148, 82], [66, 224]] ------------------------------ Epoch 056 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.546854 - Iter 024 / 025, Loss: 0.429678 * Train accuracy / confusion: 74.75% / [[242, 111], [91, 356]], * Val accuracy / confusion: 72.31% / [[144, 86], [58, 232]] ------------------------------ Epoch 057 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.479946 - Iter 024 / 025, Loss: 0.510658 * Train accuracy / confusion: 75.25% / [[237, 120], [78, 365]], * Val accuracy / confusion: 75.19% / [[158, 72], [57, 233]] ------------------------------ Epoch 058 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.760304 - Iter 024 / 025, Loss: 0.490643 * Train accuracy / confusion: 75.38% / [[248, 111], [86, 355]], * Val accuracy / confusion: 69.62% / [[112, 118], [40, 250]] ------------------------------ Epoch 059 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.502182 - Iter 024 / 025, Loss: 0.503936 * Train accuracy / confusion: 74.25% / [[225, 130], [76, 369]], * Val accuracy / confusion: 72.50% / [[151, 79], [64, 226]] ------------------------------ Epoch 060 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.463028 - Iter 024 / 025, Loss: 0.665835 * Train accuracy / confusion: 75.00% / [[244, 115], [85, 356]], * Val accuracy / confusion: 73.27% / [[160, 70], [69, 221]] ------------------------------ Epoch 061 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.645542 - Iter 024 / 025, Loss: 0.534525 * Train accuracy / confusion: 76.75% / [[246, 107], [79, 368]], * Val accuracy / confusion: 72.31% / [[132, 98], [46, 244]] ------------------------------ Epoch 062 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.493602 - Iter 024 / 025, Loss: 0.447033 * Train accuracy / confusion: 75.00% / [[241, 115], [85, 359]], * Val accuracy / confusion: 71.73% / [[119, 111], [36, 254]] ------------------------------ Epoch 063 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.541725 - Iter 024 / 025, Loss: 0.347808 * Train accuracy / confusion: 74.38% / [[234, 121], [84, 361]], * Val accuracy / confusion: 73.08% / [[140, 90], [50, 240]] ------------------------------ Epoch 064 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.511217 - Iter 024 / 025, Loss: 0.605400 * Train accuracy / confusion: 74.50% / [[243, 115], [89, 353]], * Val accuracy / confusion: 76.15% / [[171, 59], [65, 225]] ------------------------------ Epoch 065 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.557855 - Iter 024 / 025, Loss: 0.669373 * Train accuracy / confusion: 75.50% / [[242, 116], [80, 362]], * Val accuracy / confusion: 69.81% / [[118, 112], [45, 245]] ------------------------------ Epoch 066 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.453172 - Iter 024 / 025, Loss: 0.535203 * Train accuracy / confusion: 75.50% / [[247, 110], [86, 357]], * Val accuracy / confusion: 69.23% / [[117, 113], [47, 243]] ------------------------------ Epoch 067 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.554987 - Iter 024 / 025, Loss: 0.505203 * Train accuracy / confusion: 76.12% / [[244, 115], [76, 365]], * Val accuracy / confusion: 74.23% / [[152, 78], [56, 234]] ------------------------------ Epoch 068 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.556912 - Iter 024 / 025, Loss: 0.521019 * Train accuracy / confusion: 75.38% / [[250, 106], [91, 353]], * Val accuracy / confusion: 75.00% / [[146, 84], [46, 244]] ------------------------------ Epoch 069 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.607035 - Iter 024 / 025, Loss: 0.467013 * Train accuracy / confusion: 75.50% / [[253, 106], [90, 351]], * Val accuracy / confusion: 73.27% / [[134, 96], [43, 247]] ------------------------------ Epoch 070 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.424144 - Iter 024 / 025, Loss: 0.488078 * Train accuracy / confusion: 74.25% / [[251, 113], [93, 343]], * Val accuracy / confusion: 72.50% / [[142, 88], [55, 235]] ------------------------------ Epoch 071 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.660617 - Iter 024 / 025, Loss: 0.507442 * Train accuracy / confusion: 73.50% / [[234, 123], [89, 354]], * Val accuracy / confusion: 72.12% / [[161, 69], [76, 214]] ------------------------------ Epoch 072 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.423221 - Iter 024 / 025, Loss: 0.554498 * Train accuracy / confusion: 73.50% / [[235, 119], [93, 353]], * Val accuracy / confusion: 72.50% / [[159, 71], [72, 218]] ------------------------------ Epoch 073 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.532456 - Iter 024 / 025, Loss: 0.618559 * Train accuracy / confusion: 74.62% / [[229, 125], [78, 368]], * Val accuracy / confusion: 73.85% / [[174, 56], [80, 210]] ------------------------------ Epoch 074 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.456382 - Iter 024 / 025, Loss: 0.518907 * Train accuracy / confusion: 74.38% / [[248, 111], [94, 347]], * Val accuracy / confusion: 72.50% / [[127, 103], [40, 250]] ------------------------------ Epoch 075 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.557686 - Iter 024 / 025, Loss: 0.474140 * Train accuracy / confusion: 73.62% / [[228, 126], [85, 361]], * Val accuracy / confusion: 72.12% / [[123, 107], [38, 252]] ------------------------------ Epoch 076 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.576305 - Iter 024 / 025, Loss: 0.594388 * Train accuracy / confusion: 75.62% / [[234, 122], [73, 371]], * Val accuracy / confusion: 72.88% / [[153, 77], [64, 226]] ------------------------------ Epoch 077 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.470481 - Iter 024 / 025, Loss: 0.462308 * Train accuracy / confusion: 74.38% / [[248, 109], [96, 347]], * Val accuracy / confusion: 74.62% / [[153, 77], [55, 235]] ------------------------------ Epoch 078 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.434171 - Iter 024 / 025, Loss: 0.750317 * Train accuracy / confusion: 72.88% / [[218, 138], [79, 365]], * Val accuracy / confusion: 71.35% / [[123, 107], [42, 248]] ------------------------------ Epoch 079 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.492291 - Iter 024 / 025, Loss: 0.503930 * Train accuracy / confusion: 75.50% / [[245, 111], [85, 359]], * Val accuracy / confusion: 70.38% / [[124, 106], [48, 242]] ------------------------------ Epoch 080 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.623787 - Iter 024 / 025, Loss: 0.652953 * Train accuracy / confusion: 75.12% / [[245, 108], [91, 356]], * Val accuracy / confusion: 72.50% / [[122, 108], [35, 255]] ------------------------------ Epoch 081 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.700180 - Iter 024 / 025, Loss: 0.544425 * Train accuracy / confusion: 75.88% / [[249, 108], [85, 358]], * Val accuracy / confusion: 73.27% / [[145, 85], [54, 236]] ------------------------------ Epoch 082 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.547412 - Iter 024 / 025, Loss: 0.513224 * Train accuracy / confusion: 75.12% / [[236, 117], [82, 365]], * Val accuracy / confusion: 70.38% / [[167, 63], [91, 199]] ------------------------------ Epoch 083 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.566009 - Iter 024 / 025, Loss: 0.434519 * Train accuracy / confusion: 76.00% / [[250, 109], [83, 358]], * Val accuracy / confusion: 74.04% / [[144, 86], [49, 241]] ------------------------------ Epoch 084 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.590656 - Iter 024 / 025, Loss: 0.592654 * Train accuracy / confusion: 73.12% / [[246, 111], [104, 339]], * Val accuracy / confusion: 72.12% / [[146, 84], [61, 229]] ------------------------------ Epoch 085 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.438104 - Iter 024 / 025, Loss: 0.374369 * Train accuracy / confusion: 75.88% / [[256, 104], [89, 351]], * Val accuracy / confusion: 74.81% / [[168, 62], [69, 221]] ------------------------------ Epoch 086 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.381750 - Iter 024 / 025, Loss: 0.504375 * Train accuracy / confusion: 75.12% / [[241, 119], [80, 360]], * Val accuracy / confusion: 71.92% / [[133, 97], [49, 241]] ------------------------------ Epoch 087 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.690755 - Iter 024 / 025, Loss: 0.559654 * Train accuracy / confusion: 75.50% / [[251, 105], [91, 353]], * Val accuracy / confusion: 70.38% / [[117, 113], [41, 249]] ------------------------------ Epoch 088 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.524504 - Iter 024 / 025, Loss: 0.478171 * Train accuracy / confusion: 77.00% / [[247, 110], [74, 369]], * Val accuracy / confusion: 73.46% / [[144, 86], [52, 238]] ------------------------------ Epoch 089 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.380243 - Iter 024 / 025, Loss: 0.507756 * Train accuracy / confusion: 75.88% / [[261, 100], [93, 346]], * Val accuracy / confusion: 72.69% / [[157, 73], [69, 221]] ------------------------------ Epoch 090 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.468566 - Iter 024 / 025, Loss: 0.465293 * Train accuracy / confusion: 74.25% / [[223, 132], [74, 371]], * Val accuracy / confusion: 69.23% / [[119, 111], [49, 241]] ------------------------------ Epoch 091 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.470057 - Iter 024 / 025, Loss: 0.499976 * Train accuracy / confusion: 73.75% / [[241, 119], [91, 349]], * Val accuracy / confusion: 72.69% / [[160, 70], [72, 218]] ------------------------------ Epoch 092 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.511365 - Iter 024 / 025, Loss: 0.454378 * Train accuracy / confusion: 76.12% / [[252, 109], [82, 357]], * Val accuracy / confusion: 72.12% / [[128, 102], [43, 247]] ------------------------------ Epoch 093 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.651954 - Iter 024 / 025, Loss: 0.764974 * Train accuracy / confusion: 74.00% / [[237, 117], [91, 355]], * Val accuracy / confusion: 71.92% / [[125, 105], [41, 249]] ------------------------------ Epoch 094 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.406104 - Iter 024 / 025, Loss: 0.318883 * Train accuracy / confusion: 77.50% / [[253, 98], [82, 367]], * Val accuracy / confusion: 74.62% / [[144, 86], [46, 244]] ------------------------------ Epoch 095 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.484217 - Iter 024 / 025, Loss: 0.513085 * Train accuracy / confusion: 76.50% / [[236, 117], [71, 376]], * Val accuracy / confusion: 69.42% / [[176, 54], [105, 185]] ------------------------------ Epoch 096 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.707081 - Iter 024 / 025, Loss: 0.462327 * Train accuracy / confusion: 73.25% / [[227, 127], [87, 359]], * Val accuracy / confusion: 69.81% / [[116, 114], [43, 247]] ------------------------------ Epoch 097 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.370889 - Iter 024 / 025, Loss: 0.443185 * Train accuracy / confusion: 77.75% / [[257, 101], [77, 365]], * Val accuracy / confusion: 69.62% / [[113, 117], [41, 249]] ------------------------------ Epoch 098 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.347419 - Iter 024 / 025, Loss: 0.610705 * Train accuracy / confusion: 75.75% / [[238, 117], [77, 368]], * Val accuracy / confusion: 70.77% / [[169, 61], [91, 199]] ------------------------------ Epoch 099 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.515744 - Iter 024 / 025, Loss: 0.525612 * Train accuracy / confusion: 77.75% / [[243, 112], [66, 379]], * Val accuracy / confusion: 71.73% / [[129, 101], [46, 244]] ------------------------------ Epoch 100 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.668732 - Iter 024 / 025, Loss: 0.466152 * Train accuracy / confusion: 74.00% / [[241, 115], [93, 351]], * Val accuracy / confusion: 73.85% / [[136, 94], [42, 248]] ------------------------------ Epoch 101 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.639444 - Iter 024 / 025, Loss: 0.635806 * Train accuracy / confusion: 77.38% / [[251, 106], [75, 368]], * Val accuracy / confusion: 72.69% / [[151, 79], [63, 227]] ------------------------------ Epoch 102 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.448606 - Iter 024 / 025, Loss: 0.638544 * Train accuracy / confusion: 77.75% / [[252, 106], [72, 370]], * Val accuracy / confusion: 72.69% / [[134, 96], [46, 244]] ------------------------------ Epoch 103 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.451060 - Iter 024 / 025, Loss: 0.599915 * Train accuracy / confusion: 77.88% / [[258, 95], [82, 365]], * Val accuracy / confusion: 72.12% / [[178, 52], [93, 197]] ------------------------------ Epoch 104 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.594596 - Iter 024 / 025, Loss: 0.881854 * Train accuracy / confusion: 74.88% / [[240, 121], [80, 359]], * Val accuracy / confusion: 71.15% / [[140, 90], [60, 230]] ------------------------------ Epoch 105 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.757657 - Iter 024 / 025, Loss: 0.578806 * Train accuracy / confusion: 76.38% / [[262, 99], [90, 349]], * Val accuracy / confusion: 73.85% / [[142, 88], [48, 242]] ------------------------------ Epoch 106 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.638866 - Iter 024 / 025, Loss: 0.487406 * Train accuracy / confusion: 74.88% / [[251, 105], [96, 348]], * Val accuracy / confusion: 72.88% / [[137, 93], [48, 242]] ------------------------------ Epoch 107 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.385823 - Iter 024 / 025, Loss: 0.885560 * Train accuracy / confusion: 74.50% / [[243, 113], [91, 353]], * Val accuracy / confusion: 74.04% / [[154, 76], [59, 231]] ------------------------------ Epoch 108 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.624702 - Iter 024 / 025, Loss: 0.577274 * Train accuracy / confusion: 76.12% / [[249, 106], [85, 360]], * Val accuracy / confusion: 72.88% / [[173, 57], [84, 206]] ------------------------------ Epoch 109 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.495556 - Iter 024 / 025, Loss: 0.351959 * Train accuracy / confusion: 76.62% / [[250, 104], [83, 363]], * Val accuracy / confusion: 72.50% / [[132, 98], [45, 245]] ------------------------------ Epoch 110 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.464078 - Iter 024 / 025, Loss: 0.465666 * Train accuracy / confusion: 75.38% / [[252, 109], [88, 351]], * Val accuracy / confusion: 72.69% / [[147, 83], [59, 231]] ------------------------------ Epoch 111 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.411749 - Iter 024 / 025, Loss: 0.476082 * Train accuracy / confusion: 77.50% / [[264, 99], [81, 356]], * Val accuracy / confusion: 70.96% / [[120, 110], [41, 249]] ------------------------------ Epoch 112 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.424475 - Iter 024 / 025, Loss: 0.778651 * Train accuracy / confusion: 76.25% / [[236, 119], [71, 374]], * Val accuracy / confusion: 72.12% / [[143, 87], [58, 232]] ------------------------------ Epoch 113 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.419707 - Iter 024 / 025, Loss: 0.666830 * Train accuracy / confusion: 77.12% / [[278, 77], [106, 339]], * Val accuracy / confusion: 72.50% / [[147, 83], [60, 230]] ------------------------------ Epoch 114 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.589922 - Iter 024 / 025, Loss: 0.628419 * Train accuracy / confusion: 74.38% / [[247, 112], [93, 348]], * Val accuracy / confusion: 73.65% / [[166, 64], [73, 217]] ------------------------------ Epoch 115 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.388688 - Iter 024 / 025, Loss: 0.461505 * Train accuracy / confusion: 78.62% / [[263, 95], [76, 366]], * Val accuracy / confusion: 71.54% / [[140, 90], [58, 232]] ------------------------------ Epoch 116 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.351824 - Iter 024 / 025, Loss: 0.488108 * Train accuracy / confusion: 76.88% / [[260, 97], [88, 355]], * Val accuracy / confusion: 69.62% / [[119, 111], [47, 243]] ------------------------------ Epoch 117 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.368587 - Iter 024 / 025, Loss: 0.444836 * Train accuracy / confusion: 77.25% / [[266, 91], [91, 352]], * Val accuracy / confusion: 71.92% / [[154, 76], [70, 220]] ------------------------------ Epoch 118 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.469282 - Iter 024 / 025, Loss: 0.339577 * Train accuracy / confusion: 77.50% / [[264, 92], [88, 356]], * Val accuracy / confusion: 69.42% / [[106, 124], [35, 255]] ------------------------------ Epoch 119 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.405099 - Iter 024 / 025, Loss: 0.540731 * Train accuracy / confusion: 76.12% / [[248, 107], [84, 361]], * Val accuracy / confusion: 71.35% / [[153, 77], [72, 218]] ------------------------------ Epoch 120 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.421424 - Iter 024 / 025, Loss: 0.599387 * Train accuracy / confusion: 75.75% / [[257, 101], [93, 349]], * Val accuracy / confusion: 70.19% / [[134, 96], [59, 231]] ------------------------------ Epoch 121 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.506297 - Iter 024 / 025, Loss: 0.466086 * Train accuracy / confusion: 76.00% / [[246, 116], [76, 362]], * Val accuracy / confusion: 72.69% / [[172, 58], [84, 206]] ------------------------------ Epoch 122 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.414737 - Iter 024 / 025, Loss: 0.496885 * Train accuracy / confusion: 77.25% / [[253, 102], [80, 365]], * Val accuracy / confusion: 72.31% / [[141, 89], [55, 235]] ------------------------------ Epoch 123 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.393011 - Iter 024 / 025, Loss: 0.677451 * Train accuracy / confusion: 76.12% / [[266, 94], [97, 343]], * Val accuracy / confusion: 71.54% / [[142, 88], [60, 230]] ------------------------------ Epoch 124 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.527776 - Iter 024 / 025, Loss: 0.464403 * Train accuracy / confusion: 75.62% / [[241, 115], [80, 364]], * Val accuracy / confusion: 70.00% / [[135, 95], [61, 229]] ------------------------------ Epoch 125 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.372978 - Iter 024 / 025, Loss: 0.392063 * Train accuracy / confusion: 76.62% / [[265, 96], [91, 348]], * Val accuracy / confusion: 70.77% / [[121, 109], [43, 247]] ------------------------------ Epoch 126 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.445833 - Iter 024 / 025, Loss: 0.744919 * Train accuracy / confusion: 76.25% / [[245, 111], [79, 365]], * Val accuracy / confusion: 72.88% / [[156, 74], [67, 223]] ------------------------------ Epoch 127 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.399297 - Iter 024 / 025, Loss: 0.553387 * Train accuracy / confusion: 75.62% / [[247, 110], [85, 358]], * Val accuracy / confusion: 73.27% / [[146, 84], [55, 235]] ------------------------------ Epoch 128 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.357100 - Iter 024 / 025, Loss: 0.545523 * Train accuracy / confusion: 77.88% / [[270, 91], [86, 353]], * Val accuracy / confusion: 71.35% / [[155, 75], [74, 216]] ------------------------------ Epoch 129 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.460414 - Iter 024 / 025, Loss: 0.374512 * Train accuracy / confusion: 78.25% / [[259, 96], [78, 367]], * Val accuracy / confusion: 74.23% / [[149, 81], [53, 237]] ------------------------------ Epoch 130 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.510601 - Iter 024 / 025, Loss: 0.546201 * Train accuracy / confusion: 77.62% / [[262, 93], [86, 359]], * Val accuracy / confusion: 70.00% / [[175, 55], [101, 189]] ------------------------------ Epoch 131 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.370531 - Iter 024 / 025, Loss: 0.411113 * Train accuracy / confusion: 75.62% / [[257, 99], [96, 348]], * Val accuracy / confusion: 74.62% / [[168, 62], [70, 220]] ------------------------------ Epoch 132 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.385723 - Iter 024 / 025, Loss: 0.503534 * Train accuracy / confusion: 75.62% / [[259, 101], [94, 346]], * Val accuracy / confusion: 72.50% / [[157, 73], [70, 220]] ------------------------------ Epoch 133 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.445601 - Iter 024 / 025, Loss: 0.513112 * Train accuracy / confusion: 75.75% / [[256, 100], [94, 350]], * Val accuracy / confusion: 70.19% / [[171, 59], [96, 194]] ------------------------------ Epoch 134 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.360886 - Iter 024 / 025, Loss: 0.482784 * Train accuracy / confusion: 78.62% / [[272, 87], [84, 357]], * Val accuracy / confusion: 68.27% / [[148, 82], [83, 207]] ------------------------------ Epoch 135 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.499590 - Iter 024 / 025, Loss: 0.495948 * Train accuracy / confusion: 77.00% / [[259, 100], [84, 357]], * Val accuracy / confusion: 69.81% / [[110, 120], [37, 253]] ------------------------------ Epoch 136 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.457837 - Iter 024 / 025, Loss: 0.656337 * Train accuracy / confusion: 74.75% / [[239, 119], [83, 359]], * Val accuracy / confusion: 75.96% / [[165, 65], [60, 230]] ------------------------------ Epoch 137 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.508782 - Iter 024 / 025, Loss: 0.347938 * Train accuracy / confusion: 77.25% / [[264, 94], [88, 354]], * Val accuracy / confusion: 71.15% / [[160, 70], [80, 210]] ------------------------------ Epoch 138 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.494695 - Iter 024 / 025, Loss: 0.435317 * Train accuracy / confusion: 75.12% / [[248, 104], [95, 353]], * Val accuracy / confusion: 72.31% / [[165, 65], [79, 211]] ------------------------------ Epoch 139 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.438063 - Iter 024 / 025, Loss: 0.603754 * Train accuracy / confusion: 76.00% / [[247, 105], [87, 361]], * Val accuracy / confusion: 67.31% / [[98, 132], [38, 252]] ------------------------------ Epoch 140 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.545659 - Iter 024 / 025, Loss: 0.587259 * Train accuracy / confusion: 75.50% / [[248, 109], [87, 356]], * Val accuracy / confusion: 71.73% / [[126, 104], [43, 247]] ------------------------------ Epoch 141 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.725215 - Iter 024 / 025, Loss: 0.485305 * Train accuracy / confusion: 77.00% / [[260, 93], [91, 356]], * Val accuracy / confusion: 72.12% / [[141, 89], [56, 234]] ------------------------------ Epoch 142 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.481419 - Iter 024 / 025, Loss: 0.485994 * Train accuracy / confusion: 77.00% / [[247, 106], [78, 369]], * Val accuracy / confusion: 68.85% / [[147, 83], [79, 211]] ------------------------------ Epoch 143 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.396709 - Iter 024 / 025, Loss: 0.470630 * Train accuracy / confusion: 76.38% / [[241, 108], [81, 370]], * Val accuracy / confusion: 71.73% / [[123, 107], [40, 250]] ------------------------------ Epoch 144 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.444122 - Iter 024 / 025, Loss: 0.590010 * Train accuracy / confusion: 78.88% / [[268, 90], [79, 363]], * Val accuracy / confusion: 72.12% / [[155, 75], [70, 220]] ------------------------------ Epoch 145 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.439447 - Iter 024 / 025, Loss: 0.343809 * Train accuracy / confusion: 75.38% / [[255, 101], [96, 348]], * Val accuracy / confusion: 74.62% / [[160, 70], [62, 228]] ------------------------------ Epoch 146 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.385844 - Iter 024 / 025, Loss: 0.575425 * Train accuracy / confusion: 77.50% / [[259, 97], [83, 361]], * Val accuracy / confusion: 73.46% / [[157, 73], [65, 225]] ------------------------------ Epoch 147 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.500685 - Iter 024 / 025, Loss: 0.541632 * Train accuracy / confusion: 76.88% / [[237, 120], [65, 378]], * Val accuracy / confusion: 70.96% / [[162, 68], [83, 207]] ------------------------------ Epoch 148 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.490676 - Iter 024 / 025, Loss: 0.347844 * Train accuracy / confusion: 77.50% / [[253, 102], [78, 367]], * Val accuracy / confusion: 70.77% / [[143, 87], [65, 225]] ------------------------------ Epoch 149 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.402823 - Iter 024 / 025, Loss: 0.534038 * Train accuracy / confusion: 76.25% / [[248, 110], [80, 362]], * Val accuracy / confusion: 67.12% / [[102, 128], [43, 247]] ------------------------------ Epoch 150 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.634627 - Iter 024 / 025, Loss: 0.553207 * Train accuracy / confusion: 78.25% / [[271, 84], [90, 355]], * Val accuracy / confusion: 68.08% / [[177, 53], [113, 177]] ------------------------------ Epoch 151 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.322625 - Iter 024 / 025, Loss: 0.585119 * Train accuracy / confusion: 75.88% / [[234, 120], [73, 373]], * Val accuracy / confusion: 69.23% / [[104, 126], [34, 256]] ------------------------------ Epoch 152 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.758457 - Iter 024 / 025, Loss: 0.432733 * Train accuracy / confusion: 77.25% / [[251, 104], [78, 367]], * Val accuracy / confusion: 70.58% / [[157, 73], [80, 210]] ------------------------------ Epoch 153 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.414849 - Iter 024 / 025, Loss: 0.472234 * Train accuracy / confusion: 78.50% / [[254, 102], [70, 374]], * Val accuracy / confusion: 67.88% / [[116, 114], [53, 237]] ------------------------------ Epoch 154 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.363681 - Iter 024 / 025, Loss: 0.494160 * Train accuracy / confusion: 76.50% / [[244, 116], [72, 368]], * Val accuracy / confusion: 72.50% / [[156, 74], [69, 221]] ------------------------------ Epoch 155 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.537027 - Iter 024 / 025, Loss: 0.627567 * Train accuracy / confusion: 77.12% / [[252, 103], [80, 365]], * Val accuracy / confusion: 69.23% / [[136, 94], [66, 224]] ------------------------------ Epoch 156 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.375143 - Iter 024 / 025, Loss: 0.435793 * Train accuracy / confusion: 79.00% / [[251, 101], [67, 381]], * Val accuracy / confusion: 70.00% / [[148, 82], [74, 216]] ------------------------------ Epoch 157 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.318623 - Iter 024 / 025, Loss: 0.600278 * Train accuracy / confusion: 77.38% / [[252, 107], [74, 367]], * Val accuracy / confusion: 70.19% / [[138, 92], [63, 227]] ------------------------------ Epoch 158 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.444297 - Iter 024 / 025, Loss: 0.452159 * Train accuracy / confusion: 76.75% / [[248, 103], [83, 366]], * Val accuracy / confusion: 68.65% / [[117, 113], [50, 240]] ------------------------------ Epoch 159 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.424950 - Iter 024 / 025, Loss: 0.443569 * Train accuracy / confusion: 77.38% / [[244, 114], [67, 375]], * Val accuracy / confusion: 70.38% / [[148, 82], [72, 218]] ------------------------------ Epoch 160 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.561690 - Iter 024 / 025, Loss: 0.477895 * Train accuracy / confusion: 77.62% / [[269, 87], [92, 352]], * Val accuracy / confusion: 70.58% / [[141, 89], [64, 226]] ------------------------------ Epoch 161 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.375154 - Iter 024 / 025, Loss: 0.453878 * Train accuracy / confusion: 76.12% / [[245, 110], [81, 364]], * Val accuracy / confusion: 70.19% / [[143, 87], [68, 222]] ------------------------------ Epoch 162 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.461910 - Iter 024 / 025, Loss: 0.450810 * Train accuracy / confusion: 78.38% / [[253, 103], [70, 374]], * Val accuracy / confusion: 70.00% / [[170, 60], [96, 194]] ------------------------------ Epoch 163 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.454648 - Iter 024 / 025, Loss: 0.392465 * Train accuracy / confusion: 78.62% / [[273, 83], [88, 356]], * Val accuracy / confusion: 67.88% / [[116, 114], [53, 237]] ------------------------------ Epoch 164 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.375861 - Iter 024 / 025, Loss: 0.450356 * Train accuracy / confusion: 76.75% / [[252, 103], [83, 362]], * Val accuracy / confusion: 71.54% / [[133, 97], [51, 239]] ------------------------------ Epoch 165 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.400467 - Iter 024 / 025, Loss: 0.620974 * Train accuracy / confusion: 79.38% / [[268, 87], [78, 367]], * Val accuracy / confusion: 73.08% / [[143, 87], [53, 237]] ------------------------------ Epoch 166 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.417295 - Iter 024 / 025, Loss: 0.343736 * Train accuracy / confusion: 77.50% / [[258, 99], [81, 362]], * Val accuracy / confusion: 71.35% / [[136, 94], [55, 235]] ------------------------------ Epoch 167 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.453034 - Iter 024 / 025, Loss: 0.502349 * Train accuracy / confusion: 76.88% / [[245, 112], [73, 370]], * Val accuracy / confusion: 69.42% / [[102, 128], [31, 259]] ------------------------------ Epoch 168 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.353408 - Iter 024 / 025, Loss: 0.511521 * Train accuracy / confusion: 78.62% / [[266, 90], [81, 363]], * Val accuracy / confusion: 72.31% / [[144, 86], [58, 232]] ------------------------------ Epoch 169 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.453624 - Iter 024 / 025, Loss: 0.397616 * Train accuracy / confusion: 77.62% / [[251, 107], [72, 370]], * Val accuracy / confusion: 70.77% / [[145, 85], [67, 223]] ------------------------------ Epoch 170 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.459894 - Iter 024 / 025, Loss: 0.380583 * Train accuracy / confusion: 76.25% / [[252, 102], [88, 358]], * Val accuracy / confusion: 71.15% / [[137, 93], [57, 233]] ------------------------------ Epoch 171 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.456006 - Iter 024 / 025, Loss: 0.650793 * Train accuracy / confusion: 79.12% / [[251, 109], [58, 382]], * Val accuracy / confusion: 70.38% / [[129, 101], [53, 237]] ------------------------------ Epoch 172 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.457216 - Iter 024 / 025, Loss: 0.374143 * Train accuracy / confusion: 79.12% / [[272, 88], [79, 361]], * Val accuracy / confusion: 70.38% / [[139, 91], [63, 227]] ------------------------------ Epoch 173 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.463273 - Iter 024 / 025, Loss: 0.438040 * Train accuracy / confusion: 77.75% / [[265, 87], [91, 357]], * Val accuracy / confusion: 72.31% / [[150, 80], [64, 226]] ------------------------------ Epoch 174 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.387421 - Iter 024 / 025, Loss: 0.350162 * Train accuracy / confusion: 80.12% / [[264, 90], [69, 377]], * Val accuracy / confusion: 71.15% / [[150, 80], [70, 220]] ------------------------------ Epoch 175 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.458873 - Iter 024 / 025, Loss: 0.658632 * Train accuracy / confusion: 76.38% / [[263, 94], [95, 348]], * Val accuracy / confusion: 70.00% / [[142, 88], [68, 222]] ------------------------------ Epoch 176 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.363552 - Iter 024 / 025, Loss: 0.479383 * Train accuracy / confusion: 78.25% / [[275, 85], [89, 351]], * Val accuracy / confusion: 67.12% / [[105, 125], [46, 244]] ------------------------------ Epoch 177 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.472392 - Iter 024 / 025, Loss: 0.534213 * Train accuracy / confusion: 78.50% / [[259, 93], [79, 369]], * Val accuracy / confusion: 70.96% / [[156, 74], [77, 213]] ------------------------------ Epoch 178 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.429956 - Iter 024 / 025, Loss: 0.499129 * Train accuracy / confusion: 78.50% / [[252, 103], [69, 376]], * Val accuracy / confusion: 66.54% / [[89, 141], [33, 257]] ------------------------------ Epoch 179 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.270070 - Iter 024 / 025, Loss: 0.418628 * Train accuracy / confusion: 80.38% / [[262, 92], [65, 381]], * Val accuracy / confusion: 68.46% / [[107, 123], [41, 249]] ------------------------------ Epoch 180 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.389774 - Iter 024 / 025, Loss: 0.597014 * Train accuracy / confusion: 79.00% / [[258, 101], [67, 374]], * Val accuracy / confusion: 71.15% / [[118, 112], [38, 252]] ------------------------------ Epoch 181 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.425181 - Iter 024 / 025, Loss: 0.594298 * Train accuracy / confusion: 79.12% / [[269, 86], [81, 364]], * Val accuracy / confusion: 70.58% / [[160, 70], [83, 207]] ------------------------------ Epoch 182 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.554406 - Iter 024 / 025, Loss: 0.376444 * Train accuracy / confusion: 77.62% / [[258, 102], [77, 363]], * Val accuracy / confusion: 70.96% / [[176, 54], [97, 193]] ------------------------------ Epoch 183 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.418218 - Iter 024 / 025, Loss: 0.382980 * Train accuracy / confusion: 77.50% / [[250, 107], [73, 370]], * Val accuracy / confusion: 67.88% / [[125, 105], [62, 228]] ------------------------------ Epoch 184 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.342852 - Iter 024 / 025, Loss: 0.384992 * Train accuracy / confusion: 78.00% / [[260, 93], [83, 364]], * Val accuracy / confusion: 70.00% / [[172, 58], [98, 192]] ------------------------------ Epoch 185 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.517096 - Iter 024 / 025, Loss: 0.291902 * Train accuracy / confusion: 76.88% / [[256, 101], [84, 359]], * Val accuracy / confusion: 70.96% / [[115, 115], [36, 254]] ------------------------------ Epoch 186 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.414973 - Iter 024 / 025, Loss: 0.471964 * Train accuracy / confusion: 78.00% / [[244, 103], [73, 380]], * Val accuracy / confusion: 71.54% / [[143, 87], [61, 229]] ------------------------------ Epoch 187 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.431960 - Iter 024 / 025, Loss: 0.405201 * Train accuracy / confusion: 77.00% / [[239, 118], [66, 377]], * Val accuracy / confusion: 70.58% / [[128, 102], [51, 239]] ------------------------------ Epoch 188 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.303130 - Iter 024 / 025, Loss: 0.657325 * Train accuracy / confusion: 78.00% / [[263, 91], [85, 361]], * Val accuracy / confusion: 71.73% / [[145, 85], [62, 228]] ------------------------------ Epoch 189 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.448888 - Iter 024 / 025, Loss: 0.399146 * Train accuracy / confusion: 77.25% / [[258, 97], [85, 360]], * Val accuracy / confusion: 70.96% / [[138, 92], [59, 231]] ------------------------------ Epoch 190 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.482440 - Iter 024 / 025, Loss: 0.568651 * Train accuracy / confusion: 79.25% / [[267, 90], [76, 367]], * Val accuracy / confusion: 71.35% / [[134, 96], [53, 237]] ------------------------------ Epoch 191 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.336544 - Iter 024 / 025, Loss: 0.482433 * Train accuracy / confusion: 79.25% / [[266, 93], [73, 368]], * Val accuracy / confusion: 70.58% / [[163, 67], [86, 204]] ------------------------------ Epoch 192 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.597052 - Iter 024 / 025, Loss: 0.463484 * Train accuracy / confusion: 78.00% / [[262, 96], [80, 362]], * Val accuracy / confusion: 71.92% / [[140, 90], [56, 234]] ------------------------------ Epoch 193 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.429290 - Iter 024 / 025, Loss: 0.378880 * Train accuracy / confusion: 81.50% / [[276, 81], [67, 376]], * Val accuracy / confusion: 73.46% / [[160, 70], [68, 222]] ------------------------------ Epoch 194 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.490395 - Iter 024 / 025, Loss: 0.653041 * Train accuracy / confusion: 77.25% / [[253, 102], [80, 365]], * Val accuracy / confusion: 70.19% / [[139, 91], [64, 226]] ------------------------------ Epoch 195 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.345768 - Iter 024 / 025, Loss: 0.469654 * Train accuracy / confusion: 78.50% / [[267, 88], [84, 361]], * Val accuracy / confusion: 67.50% / [[117, 113], [56, 234]] ------------------------------ Epoch 196 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.540495 - Iter 024 / 025, Loss: 0.606496 * Train accuracy / confusion: 78.38% / [[268, 88], [85, 359]], * Val accuracy / confusion: 73.85% / [[180, 50], [86, 204]] ------------------------------ Epoch 197 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.462319 - Iter 024 / 025, Loss: 0.632632 * Train accuracy / confusion: 78.88% / [[257, 97], [72, 374]], * Val accuracy / confusion: 72.50% / [[145, 85], [58, 232]] ------------------------------ Epoch 198 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.567888 - Iter 024 / 025, Loss: 0.516802 * Train accuracy / confusion: 76.38% / [[259, 102], [87, 352]], * Val accuracy / confusion: 71.92% / [[155, 75], [71, 219]] ------------------------------ Epoch 199 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.673456 - Iter 024 / 025, Loss: 0.493966 * Train accuracy / confusion: 78.38% / [[259, 100], [73, 368]], * Val accuracy / confusion: 68.27% / [[115, 115], [50, 240]] ------------------------------ Epoch 200 / 500, Learning rate: 1.00e-02 ------------------------------ - Iter 012 / 025, Loss: 0.691962 - Iter 024 / 025, Loss: 0.399592 * Train accuracy / confusion: 77.88% / [[268, 89], [88, 355]], * Val accuracy / confusion: 70.19% / [[152, 78], [77, 213]] ------------------------------ Epoch 201 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.385739 - Iter 024 / 025, Loss: 0.516220 * Train accuracy / confusion: 78.25% / [[263, 97], [77, 363]], * Val accuracy / confusion: 74.81% / [[160, 70], [61, 229]] ------------------------------ Epoch 202 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517724 - Iter 024 / 025, Loss: 0.398612 * Train accuracy / confusion: 79.00% / [[263, 90], [78, 369]], * Val accuracy / confusion: 71.15% / [[148, 82], [68, 222]] ------------------------------ Epoch 203 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.440979 - Iter 024 / 025, Loss: 0.556168 * Train accuracy / confusion: 79.88% / [[265, 90], [71, 374]], * Val accuracy / confusion: 70.19% / [[131, 99], [56, 234]] ------------------------------ Epoch 204 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.459293 - Iter 024 / 025, Loss: 0.486915 * Train accuracy / confusion: 77.75% / [[261, 95], [83, 361]], * Val accuracy / confusion: 70.77% / [[136, 94], [58, 232]] ------------------------------ Epoch 205 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.397273 - Iter 024 / 025, Loss: 0.477574 * Train accuracy / confusion: 76.62% / [[252, 106], [81, 361]], * Val accuracy / confusion: 69.04% / [[140, 90], [71, 219]] ------------------------------ Epoch 206 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.549749 - Iter 024 / 025, Loss: 0.258882 * Train accuracy / confusion: 78.88% / [[268, 87], [82, 363]], * Val accuracy / confusion: 69.04% / [[137, 93], [68, 222]] ------------------------------ Epoch 207 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.455987 - Iter 024 / 025, Loss: 0.713541 * Train accuracy / confusion: 79.50% / [[264, 93], [71, 372]], * Val accuracy / confusion: 69.81% / [[140, 90], [67, 223]] ------------------------------ Epoch 208 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.425178 - Iter 024 / 025, Loss: 0.376812 * Train accuracy / confusion: 79.12% / [[271, 87], [80, 362]], * Val accuracy / confusion: 71.35% / [[136, 94], [55, 235]] ------------------------------ Epoch 209 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.381374 - Iter 024 / 025, Loss: 0.340920 * Train accuracy / confusion: 78.12% / [[259, 95], [80, 366]], * Val accuracy / confusion: 70.96% / [[150, 80], [71, 219]] ------------------------------ Epoch 210 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.411524 - Iter 024 / 025, Loss: 0.408329 * Train accuracy / confusion: 80.62% / [[273, 79], [76, 372]], * Val accuracy / confusion: 71.92% / [[146, 84], [62, 228]] ------------------------------ Epoch 211 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.537592 - Iter 024 / 025, Loss: 0.412640 * Train accuracy / confusion: 77.50% / [[257, 99], [81, 363]], * Val accuracy / confusion: 72.31% / [[149, 81], [63, 227]] ------------------------------ Epoch 212 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.349069 - Iter 024 / 025, Loss: 0.483296 * Train accuracy / confusion: 80.25% / [[273, 83], [75, 369]], * Val accuracy / confusion: 71.54% / [[150, 80], [68, 222]] ------------------------------ Epoch 213 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430941 - Iter 024 / 025, Loss: 0.275234 * Train accuracy / confusion: 79.50% / [[270, 85], [79, 366]], * Val accuracy / confusion: 70.96% / [[144, 86], [65, 225]] ------------------------------ Epoch 214 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.394250 - Iter 024 / 025, Loss: 0.390519 * Train accuracy / confusion: 78.12% / [[260, 100], [75, 365]], * Val accuracy / confusion: 69.81% / [[139, 91], [66, 224]] ------------------------------ Epoch 215 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.632334 - Iter 024 / 025, Loss: 0.540229 * Train accuracy / confusion: 79.50% / [[266, 85], [79, 370]], * Val accuracy / confusion: 70.58% / [[144, 86], [67, 223]] ------------------------------ Epoch 216 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.434275 - Iter 024 / 025, Loss: 0.548762 * Train accuracy / confusion: 80.12% / [[272, 88], [71, 369]], * Val accuracy / confusion: 71.15% / [[151, 79], [71, 219]] ------------------------------ Epoch 217 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.498294 - Iter 024 / 025, Loss: 0.347950 * Train accuracy / confusion: 80.50% / [[269, 83], [73, 375]], * Val accuracy / confusion: 71.73% / [[150, 80], [67, 223]] ------------------------------ Epoch 218 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.499617 - Iter 024 / 025, Loss: 0.608746 * Train accuracy / confusion: 77.50% / [[254, 99], [81, 366]], * Val accuracy / confusion: 68.46% / [[142, 88], [76, 214]] ------------------------------ Epoch 219 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.323143 - Iter 024 / 025, Loss: 0.446185 * Train accuracy / confusion: 78.12% / [[268, 92], [83, 357]], * Val accuracy / confusion: 71.35% / [[146, 84], [65, 225]] ------------------------------ Epoch 220 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.427901 - Iter 024 / 025, Loss: 0.444417 * Train accuracy / confusion: 79.12% / [[266, 87], [80, 367]], * Val accuracy / confusion: 69.42% / [[153, 77], [82, 208]] ------------------------------ Epoch 221 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.455033 - Iter 024 / 025, Loss: 0.517040 * Train accuracy / confusion: 78.50% / [[266, 88], [84, 362]], * Val accuracy / confusion: 71.15% / [[153, 77], [73, 217]] ------------------------------ Epoch 222 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.256699 - Iter 024 / 025, Loss: 0.340355 * Train accuracy / confusion: 80.38% / [[272, 87], [70, 371]], * Val accuracy / confusion: 71.92% / [[151, 79], [67, 223]] ------------------------------ Epoch 223 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.452587 - Iter 024 / 025, Loss: 0.348217 * Train accuracy / confusion: 79.62% / [[262, 93], [70, 375]], * Val accuracy / confusion: 69.81% / [[148, 82], [75, 215]] ------------------------------ Epoch 224 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.493861 - Iter 024 / 025, Loss: 0.503491 * Train accuracy / confusion: 78.38% / [[267, 88], [85, 360]], * Val accuracy / confusion: 71.73% / [[140, 90], [57, 233]] ------------------------------ Epoch 225 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.283864 - Iter 024 / 025, Loss: 0.433027 * Train accuracy / confusion: 79.12% / [[259, 96], [71, 374]], * Val accuracy / confusion: 72.50% / [[142, 88], [55, 235]] ------------------------------ Epoch 226 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.465833 - Iter 024 / 025, Loss: 0.520160 * Train accuracy / confusion: 79.25% / [[262, 92], [74, 372]], * Val accuracy / confusion: 69.42% / [[132, 98], [61, 229]] ------------------------------ Epoch 227 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.359627 - Iter 024 / 025, Loss: 0.338411 * Train accuracy / confusion: 78.62% / [[258, 96], [75, 371]], * Val accuracy / confusion: 70.38% / [[142, 88], [66, 224]] ------------------------------ Epoch 228 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.515417 - Iter 024 / 025, Loss: 0.513378 * Train accuracy / confusion: 78.00% / [[263, 93], [83, 361]], * Val accuracy / confusion: 70.58% / [[139, 91], [62, 228]] ------------------------------ Epoch 229 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517439 - Iter 024 / 025, Loss: 0.298940 * Train accuracy / confusion: 80.88% / [[275, 87], [66, 372]], * Val accuracy / confusion: 69.81% / [[138, 92], [65, 225]] ------------------------------ Epoch 230 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.328852 - Iter 024 / 025, Loss: 0.637970 * Train accuracy / confusion: 78.38% / [[265, 91], [82, 362]], * Val accuracy / confusion: 71.92% / [[149, 81], [65, 225]] ------------------------------ Epoch 231 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.630209 - Iter 024 / 025, Loss: 0.453852 * Train accuracy / confusion: 80.38% / [[270, 87], [70, 373]], * Val accuracy / confusion: 72.88% / [[152, 78], [63, 227]] ------------------------------ Epoch 232 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.389542 - Iter 024 / 025, Loss: 0.584854 * Train accuracy / confusion: 79.88% / [[267, 87], [74, 372]], * Val accuracy / confusion: 71.73% / [[149, 81], [66, 224]] ------------------------------ Epoch 233 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.403827 - Iter 024 / 025, Loss: 0.431078 * Train accuracy / confusion: 78.50% / [[271, 90], [82, 357]], * Val accuracy / confusion: 71.15% / [[143, 87], [63, 227]] ------------------------------ Epoch 234 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.481201 - Iter 024 / 025, Loss: 0.447860 * Train accuracy / confusion: 78.50% / [[264, 92], [80, 364]], * Val accuracy / confusion: 69.81% / [[152, 78], [79, 211]] ------------------------------ Epoch 235 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.468911 - Iter 024 / 025, Loss: 0.447785 * Train accuracy / confusion: 79.25% / [[274, 89], [77, 360]], * Val accuracy / confusion: 71.15% / [[155, 75], [75, 215]] ------------------------------ Epoch 236 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.361893 - Iter 024 / 025, Loss: 0.569164 * Train accuracy / confusion: 80.00% / [[274, 86], [74, 366]], * Val accuracy / confusion: 70.58% / [[142, 88], [65, 225]] ------------------------------ Epoch 237 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.469793 - Iter 024 / 025, Loss: 0.376411 * Train accuracy / confusion: 78.62% / [[262, 94], [77, 367]], * Val accuracy / confusion: 71.92% / [[145, 85], [61, 229]] ------------------------------ Epoch 238 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.379330 - Iter 024 / 025, Loss: 0.349744 * Train accuracy / confusion: 80.88% / [[278, 80], [73, 369]], * Val accuracy / confusion: 69.42% / [[141, 89], [70, 220]] ------------------------------ Epoch 239 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.300196 - Iter 024 / 025, Loss: 0.406669 * Train accuracy / confusion: 79.62% / [[272, 87], [76, 365]], * Val accuracy / confusion: 70.77% / [[141, 89], [63, 227]] ------------------------------ Epoch 240 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433213 - Iter 024 / 025, Loss: 0.442167 * Train accuracy / confusion: 78.50% / [[270, 87], [85, 358]], * Val accuracy / confusion: 72.88% / [[149, 81], [60, 230]] ------------------------------ Epoch 241 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.516004 - Iter 024 / 025, Loss: 0.488539 * Train accuracy / confusion: 79.62% / [[266, 95], [68, 371]], * Val accuracy / confusion: 70.00% / [[147, 83], [73, 217]] ------------------------------ Epoch 242 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.522929 - Iter 024 / 025, Loss: 0.279227 * Train accuracy / confusion: 80.25% / [[270, 90], [68, 372]], * Val accuracy / confusion: 71.15% / [[150, 80], [70, 220]] ------------------------------ Epoch 243 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.346815 - Iter 024 / 025, Loss: 0.282612 * Train accuracy / confusion: 80.88% / [[277, 82], [71, 370]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 244 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.467951 - Iter 024 / 025, Loss: 0.332329 * Train accuracy / confusion: 80.62% / [[272, 81], [74, 373]], * Val accuracy / confusion: 70.38% / [[139, 91], [63, 227]] ------------------------------ Epoch 245 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.577146 - Iter 024 / 025, Loss: 0.370171 * Train accuracy / confusion: 79.38% / [[272, 83], [82, 363]], * Val accuracy / confusion: 71.92% / [[148, 82], [64, 226]] ------------------------------ Epoch 246 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.416851 - Iter 024 / 025, Loss: 0.432035 * Train accuracy / confusion: 80.88% / [[272, 84], [69, 375]], * Val accuracy / confusion: 72.31% / [[153, 77], [67, 223]] ------------------------------ Epoch 247 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390158 - Iter 024 / 025, Loss: 0.323866 * Train accuracy / confusion: 78.50% / [[263, 91], [81, 365]], * Val accuracy / confusion: 70.96% / [[136, 94], [57, 233]] ------------------------------ Epoch 248 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.620893 - Iter 024 / 025, Loss: 0.351167 * Train accuracy / confusion: 80.50% / [[266, 87], [69, 378]], * Val accuracy / confusion: 71.54% / [[156, 74], [74, 216]] ------------------------------ Epoch 249 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.553541 - Iter 024 / 025, Loss: 0.408336 * Train accuracy / confusion: 80.62% / [[268, 90], [65, 377]], * Val accuracy / confusion: 70.96% / [[148, 82], [69, 221]] ------------------------------ Epoch 250 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.457935 - Iter 024 / 025, Loss: 0.472733 * Train accuracy / confusion: 78.62% / [[269, 90], [81, 360]], * Val accuracy / confusion: 71.73% / [[150, 80], [67, 223]] ------------------------------ Epoch 251 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.484861 - Iter 024 / 025, Loss: 0.373119 * Train accuracy / confusion: 79.50% / [[269, 88], [76, 367]], * Val accuracy / confusion: 71.15% / [[146, 84], [66, 224]] ------------------------------ Epoch 252 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.534063 - Iter 024 / 025, Loss: 0.358779 * Train accuracy / confusion: 80.88% / [[273, 85], [68, 374]], * Val accuracy / confusion: 71.35% / [[149, 81], [68, 222]] ------------------------------ Epoch 253 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.367927 - Iter 024 / 025, Loss: 0.388817 * Train accuracy / confusion: 79.88% / [[269, 90], [71, 370]], * Val accuracy / confusion: 72.12% / [[149, 81], [64, 226]] ------------------------------ Epoch 254 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.388149 - Iter 024 / 025, Loss: 0.478938 * Train accuracy / confusion: 80.38% / [[273, 85], [72, 370]], * Val accuracy / confusion: 71.73% / [[144, 86], [61, 229]] ------------------------------ Epoch 255 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.360062 - Iter 024 / 025, Loss: 0.292267 * Train accuracy / confusion: 79.25% / [[265, 92], [74, 369]], * Val accuracy / confusion: 70.96% / [[140, 90], [61, 229]] ------------------------------ Epoch 256 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.344591 - Iter 024 / 025, Loss: 0.461695 * Train accuracy / confusion: 81.25% / [[273, 82], [68, 377]], * Val accuracy / confusion: 70.96% / [[136, 94], [57, 233]] ------------------------------ Epoch 257 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.263211 - Iter 024 / 025, Loss: 0.581612 * Train accuracy / confusion: 80.38% / [[270, 89], [68, 373]], * Val accuracy / confusion: 73.65% / [[160, 70], [67, 223]] ------------------------------ Epoch 258 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.327878 - Iter 024 / 025, Loss: 0.407394 * Train accuracy / confusion: 80.38% / [[271, 84], [73, 372]], * Val accuracy / confusion: 71.35% / [[148, 82], [67, 223]] ------------------------------ Epoch 259 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.373978 - Iter 024 / 025, Loss: 0.448024 * Train accuracy / confusion: 81.50% / [[272, 85], [63, 380]], * Val accuracy / confusion: 71.15% / [[151, 79], [71, 219]] ------------------------------ Epoch 260 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.346312 - Iter 024 / 025, Loss: 0.445703 * Train accuracy / confusion: 78.88% / [[267, 90], [79, 364]], * Val accuracy / confusion: 70.96% / [[152, 78], [73, 217]] ------------------------------ Epoch 261 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.613828 - Iter 024 / 025, Loss: 0.512948 * Train accuracy / confusion: 79.25% / [[267, 94], [72, 367]], * Val accuracy / confusion: 71.73% / [[145, 85], [62, 228]] ------------------------------ Epoch 262 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.342007 - Iter 024 / 025, Loss: 0.523402 * Train accuracy / confusion: 78.38% / [[263, 95], [78, 364]], * Val accuracy / confusion: 71.15% / [[145, 85], [65, 225]] ------------------------------ Epoch 263 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.509344 - Iter 024 / 025, Loss: 0.344277 * Train accuracy / confusion: 80.38% / [[273, 81], [76, 370]], * Val accuracy / confusion: 72.12% / [[150, 80], [65, 225]] ------------------------------ Epoch 264 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.429301 - Iter 024 / 025, Loss: 0.534887 * Train accuracy / confusion: 79.75% / [[269, 89], [73, 369]], * Val accuracy / confusion: 72.12% / [[155, 75], [70, 220]] ------------------------------ Epoch 265 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.402121 - Iter 024 / 025, Loss: 0.400601 * Train accuracy / confusion: 81.75% / [[275, 79], [67, 379]], * Val accuracy / confusion: 71.15% / [[145, 85], [65, 225]] ------------------------------ Epoch 266 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.352616 - Iter 024 / 025, Loss: 0.416382 * Train accuracy / confusion: 79.88% / [[268, 84], [77, 371]], * Val accuracy / confusion: 74.42% / [[157, 73], [60, 230]] ------------------------------ Epoch 267 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.424501 - Iter 024 / 025, Loss: 0.517720 * Train accuracy / confusion: 79.12% / [[264, 89], [78, 369]], * Val accuracy / confusion: 70.38% / [[150, 80], [74, 216]] ------------------------------ Epoch 268 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.458615 - Iter 024 / 025, Loss: 0.443623 * Train accuracy / confusion: 80.75% / [[269, 85], [69, 377]], * Val accuracy / confusion: 70.58% / [[137, 93], [60, 230]] ------------------------------ Epoch 269 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.507155 - Iter 024 / 025, Loss: 0.413856 * Train accuracy / confusion: 80.25% / [[272, 85], [73, 370]], * Val accuracy / confusion: 71.73% / [[144, 86], [61, 229]] ------------------------------ Epoch 270 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.356949 - Iter 024 / 025, Loss: 0.438507 * Train accuracy / confusion: 79.75% / [[276, 80], [82, 362]], * Val accuracy / confusion: 70.58% / [[142, 88], [65, 225]] ------------------------------ Epoch 271 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.309929 - Iter 024 / 025, Loss: 0.445473 * Train accuracy / confusion: 80.62% / [[273, 89], [66, 372]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 272 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519278 - Iter 024 / 025, Loss: 0.331713 * Train accuracy / confusion: 80.00% / [[274, 82], [78, 366]], * Val accuracy / confusion: 72.31% / [[151, 79], [65, 225]] ------------------------------ Epoch 273 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.458928 - Iter 024 / 025, Loss: 0.367016 * Train accuracy / confusion: 80.88% / [[273, 82], [71, 374]], * Val accuracy / confusion: 72.31% / [[152, 78], [66, 224]] ------------------------------ Epoch 274 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.412488 - Iter 024 / 025, Loss: 0.674426 * Train accuracy / confusion: 77.88% / [[260, 101], [76, 363]], * Val accuracy / confusion: 75.19% / [[160, 70], [59, 231]] ------------------------------ Epoch 275 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.253812 - Iter 024 / 025, Loss: 0.367069 * Train accuracy / confusion: 83.12% / [[286, 71], [64, 379]], * Val accuracy / confusion: 69.81% / [[139, 91], [66, 224]] ------------------------------ Epoch 276 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.369733 - Iter 024 / 025, Loss: 0.390410 * Train accuracy / confusion: 80.50% / [[267, 81], [75, 377]], * Val accuracy / confusion: 70.19% / [[150, 80], [75, 215]] ------------------------------ Epoch 277 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.388322 - Iter 024 / 025, Loss: 0.357962 * Train accuracy / confusion: 80.25% / [[274, 87], [71, 368]], * Val accuracy / confusion: 69.62% / [[139, 91], [67, 223]] ------------------------------ Epoch 278 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.367423 - Iter 024 / 025, Loss: 0.605480 * Train accuracy / confusion: 79.75% / [[267, 83], [79, 371]], * Val accuracy / confusion: 71.92% / [[155, 75], [71, 219]] ------------------------------ Epoch 279 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.354835 - Iter 024 / 025, Loss: 0.478710 * Train accuracy / confusion: 81.50% / [[272, 79], [69, 380]], * Val accuracy / confusion: 71.15% / [[155, 75], [75, 215]] ------------------------------ Epoch 280 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.423903 - Iter 024 / 025, Loss: 0.570378 * Train accuracy / confusion: 80.88% / [[270, 85], [68, 377]], * Val accuracy / confusion: 68.85% / [[141, 89], [73, 217]] ------------------------------ Epoch 281 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.287746 - Iter 024 / 025, Loss: 0.437643 * Train accuracy / confusion: 79.38% / [[261, 99], [66, 374]], * Val accuracy / confusion: 69.42% / [[138, 92], [67, 223]] ------------------------------ Epoch 282 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.712020 - Iter 024 / 025, Loss: 0.339287 * Train accuracy / confusion: 79.12% / [[278, 82], [85, 355]], * Val accuracy / confusion: 71.15% / [[157, 73], [77, 213]] ------------------------------ Epoch 283 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.383317 - Iter 024 / 025, Loss: 0.399764 * Train accuracy / confusion: 80.12% / [[270, 87], [72, 371]], * Val accuracy / confusion: 71.15% / [[156, 74], [76, 214]] ------------------------------ Epoch 284 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.310689 - Iter 024 / 025, Loss: 0.487788 * Train accuracy / confusion: 82.38% / [[280, 73], [68, 379]], * Val accuracy / confusion: 69.42% / [[138, 92], [67, 223]] ------------------------------ Epoch 285 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.452751 - Iter 024 / 025, Loss: 0.374781 * Train accuracy / confusion: 81.00% / [[273, 82], [70, 375]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] ------------------------------ Epoch 286 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466001 - Iter 024 / 025, Loss: 0.480480 * Train accuracy / confusion: 80.50% / [[281, 76], [80, 363]], * Val accuracy / confusion: 71.92% / [[146, 84], [62, 228]] ------------------------------ Epoch 287 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.414860 - Iter 024 / 025, Loss: 0.524931 * Train accuracy / confusion: 79.88% / [[274, 76], [85, 365]], * Val accuracy / confusion: 71.92% / [[160, 70], [76, 214]] ------------------------------ Epoch 288 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.606926 - Iter 024 / 025, Loss: 0.405594 * Train accuracy / confusion: 80.62% / [[264, 89], [66, 381]], * Val accuracy / confusion: 73.65% / [[160, 70], [67, 223]] ------------------------------ Epoch 289 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.493251 - Iter 024 / 025, Loss: 0.377309 * Train accuracy / confusion: 80.75% / [[273, 83], [71, 373]], * Val accuracy / confusion: 73.08% / [[154, 76], [64, 226]] ------------------------------ Epoch 290 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.516278 - Iter 024 / 025, Loss: 0.639446 * Train accuracy / confusion: 79.12% / [[260, 93], [74, 373]], * Val accuracy / confusion: 71.35% / [[149, 81], [68, 222]] ------------------------------ Epoch 291 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.386222 - Iter 024 / 025, Loss: 0.366027 * Train accuracy / confusion: 79.50% / [[268, 88], [76, 368]], * Val accuracy / confusion: 70.96% / [[151, 79], [72, 218]] ------------------------------ Epoch 292 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.587155 - Iter 024 / 025, Loss: 0.269224 * Train accuracy / confusion: 79.88% / [[265, 90], [71, 374]], * Val accuracy / confusion: 67.88% / [[128, 102], [65, 225]] ------------------------------ Epoch 293 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.322154 - Iter 024 / 025, Loss: 0.475543 * Train accuracy / confusion: 77.88% / [[249, 111], [66, 374]], * Val accuracy / confusion: 71.73% / [[139, 91], [56, 234]] ------------------------------ Epoch 294 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.436208 - Iter 024 / 025, Loss: 0.432882 * Train accuracy / confusion: 79.38% / [[269, 89], [76, 366]], * Val accuracy / confusion: 70.00% / [[148, 82], [74, 216]] ------------------------------ Epoch 295 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.601724 - Iter 024 / 025, Loss: 0.391436 * Train accuracy / confusion: 81.75% / [[269, 86], [60, 385]], * Val accuracy / confusion: 68.85% / [[143, 87], [75, 215]] ------------------------------ Epoch 296 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.535841 - Iter 024 / 025, Loss: 0.407286 * Train accuracy / confusion: 79.00% / [[269, 92], [76, 363]], * Val accuracy / confusion: 71.54% / [[152, 78], [70, 220]] ------------------------------ Epoch 297 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.247055 - Iter 024 / 025, Loss: 0.457715 * Train accuracy / confusion: 80.75% / [[274, 87], [67, 372]], * Val accuracy / confusion: 73.27% / [[153, 77], [62, 228]] ------------------------------ Epoch 298 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.400729 - Iter 024 / 025, Loss: 0.538906 * Train accuracy / confusion: 79.88% / [[271, 85], [76, 368]], * Val accuracy / confusion: 73.65% / [[152, 78], [59, 231]] ------------------------------ Epoch 299 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.467637 - Iter 024 / 025, Loss: 0.382744 * Train accuracy / confusion: 79.88% / [[267, 90], [71, 372]], * Val accuracy / confusion: 70.96% / [[156, 74], [77, 213]] ------------------------------ Epoch 300 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.536648 - Iter 024 / 025, Loss: 0.512428 * Train accuracy / confusion: 79.25% / [[258, 98], [68, 376]], * Val accuracy / confusion: 72.88% / [[152, 78], [63, 227]] ------------------------------ Epoch 301 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.300175 - Iter 024 / 025, Loss: 0.495382 * Train accuracy / confusion: 80.62% / [[278, 77], [78, 367]], * Val accuracy / confusion: 73.08% / [[163, 67], [73, 217]] ------------------------------ Epoch 302 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466927 - Iter 024 / 025, Loss: 0.443243 * Train accuracy / confusion: 80.38% / [[274, 83], [74, 369]], * Val accuracy / confusion: 72.50% / [[146, 84], [59, 231]] ------------------------------ Epoch 303 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464906 - Iter 024 / 025, Loss: 0.263054 * Train accuracy / confusion: 83.00% / [[282, 72], [64, 382]], * Val accuracy / confusion: 72.69% / [[150, 80], [62, 228]] ------------------------------ Epoch 304 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.454927 - Iter 024 / 025, Loss: 0.601078 * Train accuracy / confusion: 79.88% / [[270, 91], [70, 369]], * Val accuracy / confusion: 73.27% / [[155, 75], [64, 226]] ------------------------------ Epoch 305 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.379163 - Iter 024 / 025, Loss: 0.355184 * Train accuracy / confusion: 81.00% / [[278, 79], [73, 370]], * Val accuracy / confusion: 71.73% / [[138, 92], [55, 235]] ------------------------------ Epoch 306 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.333451 - Iter 024 / 025, Loss: 0.381904 * Train accuracy / confusion: 80.00% / [[274, 81], [79, 366]], * Val accuracy / confusion: 69.62% / [[142, 88], [70, 220]] ------------------------------ Epoch 307 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.735439 - Iter 024 / 025, Loss: 0.450435 * Train accuracy / confusion: 79.12% / [[257, 96], [71, 376]], * Val accuracy / confusion: 70.19% / [[141, 89], [66, 224]] ------------------------------ Epoch 308 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.498326 - Iter 024 / 025, Loss: 0.626097 * Train accuracy / confusion: 80.25% / [[266, 87], [71, 376]], * Val accuracy / confusion: 69.42% / [[138, 92], [67, 223]] ------------------------------ Epoch 309 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.599591 - Iter 024 / 025, Loss: 0.663987 * Train accuracy / confusion: 78.38% / [[260, 94], [79, 367]], * Val accuracy / confusion: 71.35% / [[149, 81], [68, 222]] ------------------------------ Epoch 310 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.485886 - Iter 024 / 025, Loss: 0.491394 * Train accuracy / confusion: 81.25% / [[276, 83], [67, 374]], * Val accuracy / confusion: 71.54% / [[138, 92], [56, 234]] ------------------------------ Epoch 311 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.472432 - Iter 024 / 025, Loss: 0.526300 * Train accuracy / confusion: 80.50% / [[278, 80], [76, 366]], * Val accuracy / confusion: 69.23% / [[154, 76], [84, 206]] ------------------------------ Epoch 312 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.313900 - Iter 024 / 025, Loss: 0.389831 * Train accuracy / confusion: 80.25% / [[273, 83], [75, 369]], * Val accuracy / confusion: 69.42% / [[149, 81], [78, 212]] ------------------------------ Epoch 313 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.289706 - Iter 024 / 025, Loss: 0.513994 * Train accuracy / confusion: 79.38% / [[269, 88], [77, 366]], * Val accuracy / confusion: 69.81% / [[141, 89], [68, 222]] ------------------------------ Epoch 314 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.355061 - Iter 024 / 025, Loss: 0.484027 * Train accuracy / confusion: 80.38% / [[277, 81], [76, 366]], * Val accuracy / confusion: 72.12% / [[150, 80], [65, 225]] ------------------------------ Epoch 315 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.369786 - Iter 024 / 025, Loss: 0.333136 * Train accuracy / confusion: 81.50% / [[279, 79], [69, 373]], * Val accuracy / confusion: 73.08% / [[158, 72], [68, 222]] ------------------------------ Epoch 316 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.316138 - Iter 024 / 025, Loss: 0.414209 * Train accuracy / confusion: 81.12% / [[276, 81], [70, 373]], * Val accuracy / confusion: 69.62% / [[141, 89], [69, 221]] ------------------------------ Epoch 317 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.553539 - Iter 024 / 025, Loss: 0.389998 * Train accuracy / confusion: 81.38% / [[275, 82], [67, 376]], * Val accuracy / confusion: 74.81% / [[159, 71], [60, 230]] ------------------------------ Epoch 318 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.460509 - Iter 024 / 025, Loss: 0.350719 * Train accuracy / confusion: 79.75% / [[272, 87], [75, 366]], * Val accuracy / confusion: 73.08% / [[158, 72], [68, 222]] ------------------------------ Epoch 319 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.270236 - Iter 024 / 025, Loss: 0.321162 * Train accuracy / confusion: 80.62% / [[272, 84], [71, 373]], * Val accuracy / confusion: 75.38% / [[157, 73], [55, 235]] ------------------------------ Epoch 320 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.435157 - Iter 024 / 025, Loss: 0.403453 * Train accuracy / confusion: 80.25% / [[269, 85], [73, 373]], * Val accuracy / confusion: 73.08% / [[149, 81], [59, 231]] ------------------------------ Epoch 321 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.440468 - Iter 024 / 025, Loss: 0.555203 * Train accuracy / confusion: 78.88% / [[271, 85], [84, 360]], * Val accuracy / confusion: 71.35% / [[143, 87], [62, 228]] ------------------------------ Epoch 322 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.515152 - Iter 024 / 025, Loss: 0.442396 * Train accuracy / confusion: 80.00% / [[275, 80], [80, 365]], * Val accuracy / confusion: 71.35% / [[148, 82], [67, 223]] ------------------------------ Epoch 323 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.454139 - Iter 024 / 025, Loss: 0.523874 * Train accuracy / confusion: 80.50% / [[273, 86], [70, 371]], * Val accuracy / confusion: 71.35% / [[137, 93], [56, 234]] ------------------------------ Epoch 324 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.469257 - Iter 024 / 025, Loss: 0.419521 * Train accuracy / confusion: 80.88% / [[275, 80], [73, 372]], * Val accuracy / confusion: 70.77% / [[142, 88], [64, 226]] ------------------------------ Epoch 325 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.325530 - Iter 024 / 025, Loss: 0.526400 * Train accuracy / confusion: 80.88% / [[270, 84], [69, 377]], * Val accuracy / confusion: 70.77% / [[148, 82], [70, 220]] ------------------------------ Epoch 326 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.356781 - Iter 024 / 025, Loss: 0.517485 * Train accuracy / confusion: 81.50% / [[277, 77], [71, 375]], * Val accuracy / confusion: 71.15% / [[148, 82], [68, 222]] ------------------------------ Epoch 327 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433207 - Iter 024 / 025, Loss: 0.420735 * Train accuracy / confusion: 78.88% / [[263, 92], [77, 368]], * Val accuracy / confusion: 72.12% / [[158, 72], [73, 217]] ------------------------------ Epoch 328 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.447025 - Iter 024 / 025, Loss: 0.389770 * Train accuracy / confusion: 81.12% / [[273, 83], [68, 376]], * Val accuracy / confusion: 69.04% / [[136, 94], [67, 223]] ------------------------------ Epoch 329 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.377006 - Iter 024 / 025, Loss: 0.376427 * Train accuracy / confusion: 79.50% / [[269, 86], [78, 367]], * Val accuracy / confusion: 72.12% / [[156, 74], [71, 219]] ------------------------------ Epoch 330 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.387959 - Iter 024 / 025, Loss: 0.499183 * Train accuracy / confusion: 80.50% / [[268, 84], [72, 376]], * Val accuracy / confusion: 73.65% / [[157, 73], [64, 226]] ------------------------------ Epoch 331 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.237827 - Iter 024 / 025, Loss: 0.467392 * Train accuracy / confusion: 80.50% / [[267, 85], [71, 377]], * Val accuracy / confusion: 70.58% / [[143, 87], [66, 224]] ------------------------------ Epoch 332 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.372073 - Iter 024 / 025, Loss: 0.448275 * Train accuracy / confusion: 80.62% / [[272, 85], [70, 373]], * Val accuracy / confusion: 71.15% / [[154, 76], [74, 216]] ------------------------------ Epoch 333 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488615 - Iter 024 / 025, Loss: 0.632229 * Train accuracy / confusion: 79.88% / [[269, 88], [73, 370]], * Val accuracy / confusion: 71.15% / [[151, 79], [71, 219]] ------------------------------ Epoch 334 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477412 - Iter 024 / 025, Loss: 0.363109 * Train accuracy / confusion: 81.75% / [[276, 76], [70, 378]], * Val accuracy / confusion: 71.92% / [[152, 78], [68, 222]] ------------------------------ Epoch 335 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.387167 - Iter 024 / 025, Loss: 0.435865 * Train accuracy / confusion: 80.50% / [[266, 93], [63, 378]], * Val accuracy / confusion: 67.12% / [[138, 92], [79, 211]] ------------------------------ Epoch 336 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.332689 - Iter 024 / 025, Loss: 0.389372 * Train accuracy / confusion: 81.62% / [[271, 84], [63, 382]], * Val accuracy / confusion: 71.15% / [[140, 90], [60, 230]] ------------------------------ Epoch 337 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.335251 - Iter 024 / 025, Loss: 0.390984 * Train accuracy / confusion: 79.50% / [[269, 89], [75, 367]], * Val accuracy / confusion: 70.77% / [[143, 87], [65, 225]] ------------------------------ Epoch 338 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.350894 - Iter 024 / 025, Loss: 0.416118 * Train accuracy / confusion: 82.38% / [[281, 76], [65, 378]], * Val accuracy / confusion: 70.58% / [[142, 88], [65, 225]] ------------------------------ Epoch 339 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.400241 - Iter 024 / 025, Loss: 0.620464 * Train accuracy / confusion: 79.88% / [[274, 81], [80, 365]], * Val accuracy / confusion: 72.12% / [[164, 66], [79, 211]] ------------------------------ Epoch 340 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390896 - Iter 024 / 025, Loss: 0.311351 * Train accuracy / confusion: 80.62% / [[269, 85], [70, 376]], * Val accuracy / confusion: 74.42% / [[157, 73], [60, 230]] ------------------------------ Epoch 341 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466241 - Iter 024 / 025, Loss: 0.404318 * Train accuracy / confusion: 82.75% / [[279, 77], [61, 383]], * Val accuracy / confusion: 72.31% / [[151, 79], [65, 225]] ------------------------------ Epoch 342 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.434895 - Iter 024 / 025, Loss: 0.417813 * Train accuracy / confusion: 80.62% / [[269, 86], [69, 376]], * Val accuracy / confusion: 69.62% / [[138, 92], [66, 224]] ------------------------------ Epoch 343 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.493332 - Iter 024 / 025, Loss: 0.277016 * Train accuracy / confusion: 81.12% / [[274, 83], [68, 375]], * Val accuracy / confusion: 70.58% / [[148, 82], [71, 219]] ------------------------------ Epoch 344 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.291267 - Iter 024 / 025, Loss: 0.592552 * Train accuracy / confusion: 78.38% / [[267, 92], [81, 360]], * Val accuracy / confusion: 70.19% / [[147, 83], [72, 218]] ------------------------------ Epoch 345 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.279571 - Iter 024 / 025, Loss: 0.323442 * Train accuracy / confusion: 83.50% / [[285, 70], [62, 383]], * Val accuracy / confusion: 70.58% / [[144, 86], [67, 223]] ------------------------------ Epoch 346 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.227743 - Iter 024 / 025, Loss: 0.440480 * Train accuracy / confusion: 80.62% / [[271, 84], [71, 374]], * Val accuracy / confusion: 71.35% / [[153, 77], [72, 218]] ------------------------------ Epoch 347 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.334386 - Iter 024 / 025, Loss: 0.389922 * Train accuracy / confusion: 83.00% / [[274, 80], [56, 390]], * Val accuracy / confusion: 70.38% / [[144, 86], [68, 222]] ------------------------------ Epoch 348 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430078 - Iter 024 / 025, Loss: 0.500822 * Train accuracy / confusion: 82.38% / [[279, 81], [60, 380]], * Val accuracy / confusion: 69.04% / [[138, 92], [69, 221]] ------------------------------ Epoch 349 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.326712 - Iter 024 / 025, Loss: 0.346183 * Train accuracy / confusion: 81.62% / [[278, 74], [73, 375]], * Val accuracy / confusion: 73.08% / [[161, 69], [71, 219]] ------------------------------ Epoch 350 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.261653 - Iter 024 / 025, Loss: 0.408790 * Train accuracy / confusion: 80.25% / [[269, 86], [72, 373]], * Val accuracy / confusion: 70.00% / [[147, 83], [73, 217]] ------------------------------ Epoch 351 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.256875 - Iter 024 / 025, Loss: 0.691157 * Train accuracy / confusion: 78.75% / [[266, 87], [83, 364]], * Val accuracy / confusion: 70.38% / [[146, 84], [70, 220]] ------------------------------ Epoch 352 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.732051 - Iter 024 / 025, Loss: 0.470314 * Train accuracy / confusion: 82.38% / [[277, 79], [62, 382]], * Val accuracy / confusion: 70.77% / [[153, 77], [75, 215]] ------------------------------ Epoch 353 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483230 - Iter 024 / 025, Loss: 0.450677 * Train accuracy / confusion: 80.12% / [[271, 88], [71, 370]], * Val accuracy / confusion: 70.96% / [[148, 82], [69, 221]] ------------------------------ Epoch 354 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.370454 - Iter 024 / 025, Loss: 0.388192 * Train accuracy / confusion: 79.88% / [[266, 87], [74, 373]], * Val accuracy / confusion: 71.92% / [[161, 69], [77, 213]] ------------------------------ Epoch 355 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.355576 - Iter 024 / 025, Loss: 0.374117 * Train accuracy / confusion: 81.00% / [[277, 81], [71, 371]], * Val accuracy / confusion: 69.62% / [[135, 95], [63, 227]] ------------------------------ Epoch 356 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.515524 - Iter 024 / 025, Loss: 0.517489 * Train accuracy / confusion: 81.62% / [[274, 82], [65, 379]], * Val accuracy / confusion: 70.00% / [[141, 89], [67, 223]] ------------------------------ Epoch 357 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.359095 - Iter 024 / 025, Loss: 0.394111 * Train accuracy / confusion: 81.75% / [[278, 77], [69, 376]], * Val accuracy / confusion: 69.04% / [[146, 84], [77, 213]] ------------------------------ Epoch 358 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.620795 - Iter 024 / 025, Loss: 0.426235 * Train accuracy / confusion: 81.75% / [[283, 72], [74, 371]], * Val accuracy / confusion: 72.12% / [[152, 78], [67, 223]] ------------------------------ Epoch 359 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.311801 - Iter 024 / 025, Loss: 0.507264 * Train accuracy / confusion: 80.75% / [[278, 80], [74, 368]], * Val accuracy / confusion: 71.15% / [[152, 78], [72, 218]] ------------------------------ Epoch 360 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.307178 - Iter 024 / 025, Loss: 0.463618 * Train accuracy / confusion: 79.88% / [[272, 86], [75, 367]], * Val accuracy / confusion: 74.62% / [[151, 79], [53, 237]] ------------------------------ Epoch 361 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.355341 - Iter 024 / 025, Loss: 0.530166 * Train accuracy / confusion: 80.25% / [[268, 84], [74, 374]], * Val accuracy / confusion: 72.69% / [[152, 78], [64, 226]] ------------------------------ Epoch 362 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.432114 - Iter 024 / 025, Loss: 0.314388 * Train accuracy / confusion: 80.88% / [[281, 79], [74, 366]], * Val accuracy / confusion: 69.62% / [[142, 88], [70, 220]] ------------------------------ Epoch 363 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.219882 - Iter 024 / 025, Loss: 0.311834 * Train accuracy / confusion: 79.75% / [[274, 84], [78, 364]], * Val accuracy / confusion: 73.46% / [[164, 66], [72, 218]] ------------------------------ Epoch 364 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.378564 - Iter 024 / 025, Loss: 0.302335 * Train accuracy / confusion: 81.25% / [[276, 78], [72, 374]], * Val accuracy / confusion: 71.35% / [[153, 77], [72, 218]] ------------------------------ Epoch 365 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.245042 - Iter 024 / 025, Loss: 0.356059 * Train accuracy / confusion: 80.50% / [[273, 80], [76, 371]], * Val accuracy / confusion: 71.54% / [[141, 89], [59, 231]] ------------------------------ Epoch 366 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.482719 - Iter 024 / 025, Loss: 0.553873 * Train accuracy / confusion: 80.50% / [[267, 83], [73, 377]], * Val accuracy / confusion: 69.62% / [[152, 78], [80, 210]] ------------------------------ Epoch 367 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.384983 - Iter 024 / 025, Loss: 0.744777 * Train accuracy / confusion: 80.38% / [[266, 87], [70, 377]], * Val accuracy / confusion: 69.62% / [[144, 86], [72, 218]] ------------------------------ Epoch 368 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.349923 - Iter 024 / 025, Loss: 0.597106 * Train accuracy / confusion: 80.88% / [[268, 88], [65, 379]], * Val accuracy / confusion: 70.38% / [[144, 86], [68, 222]] ------------------------------ Epoch 369 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.413542 - Iter 024 / 025, Loss: 0.438135 * Train accuracy / confusion: 80.62% / [[264, 88], [67, 381]], * Val accuracy / confusion: 69.81% / [[146, 84], [73, 217]] ------------------------------ Epoch 370 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519329 - Iter 024 / 025, Loss: 0.382759 * Train accuracy / confusion: 80.62% / [[263, 89], [66, 382]], * Val accuracy / confusion: 70.00% / [[147, 83], [73, 217]] ------------------------------ Epoch 371 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.531725 - Iter 024 / 025, Loss: 0.386884 * Train accuracy / confusion: 76.88% / [[256, 102], [83, 359]], * Val accuracy / confusion: 70.38% / [[155, 75], [79, 211]] ------------------------------ Epoch 372 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.458406 - Iter 024 / 025, Loss: 0.481420 * Train accuracy / confusion: 81.38% / [[281, 79], [70, 370]], * Val accuracy / confusion: 70.00% / [[143, 87], [69, 221]] ------------------------------ Epoch 373 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.386904 - Iter 024 / 025, Loss: 0.448802 * Train accuracy / confusion: 79.75% / [[275, 81], [81, 363]], * Val accuracy / confusion: 69.81% / [[151, 79], [78, 212]] ------------------------------ Epoch 374 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.350359 - Iter 024 / 025, Loss: 0.354810 * Train accuracy / confusion: 80.50% / [[269, 88], [68, 375]], * Val accuracy / confusion: 73.08% / [[153, 77], [63, 227]] ------------------------------ Epoch 375 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.453803 - Iter 024 / 025, Loss: 0.339003 * Train accuracy / confusion: 81.62% / [[277, 78], [69, 376]], * Val accuracy / confusion: 70.38% / [[143, 87], [67, 223]] ------------------------------ Epoch 376 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.448071 - Iter 024 / 025, Loss: 0.461826 * Train accuracy / confusion: 80.88% / [[276, 84], [69, 371]], * Val accuracy / confusion: 71.73% / [[148, 82], [65, 225]] ------------------------------ Epoch 377 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430047 - Iter 024 / 025, Loss: 0.327389 * Train accuracy / confusion: 81.00% / [[274, 83], [69, 374]], * Val accuracy / confusion: 69.23% / [[143, 87], [73, 217]] ------------------------------ Epoch 378 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.291446 - Iter 024 / 025, Loss: 0.407048 * Train accuracy / confusion: 79.38% / [[273, 86], [79, 362]], * Val accuracy / confusion: 71.15% / [[153, 77], [73, 217]] ------------------------------ Epoch 379 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.455786 - Iter 024 / 025, Loss: 0.471159 * Train accuracy / confusion: 80.25% / [[278, 78], [80, 364]], * Val accuracy / confusion: 73.08% / [[159, 71], [69, 221]] ------------------------------ Epoch 380 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.422975 - Iter 024 / 025, Loss: 0.499297 * Train accuracy / confusion: 81.75% / [[272, 83], [63, 382]], * Val accuracy / confusion: 72.12% / [[154, 76], [69, 221]] ------------------------------ Epoch 381 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.383650 - Iter 024 / 025, Loss: 0.481609 * Train accuracy / confusion: 79.75% / [[273, 83], [79, 365]], * Val accuracy / confusion: 71.54% / [[154, 76], [72, 218]] ------------------------------ Epoch 382 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.457123 - Iter 024 / 025, Loss: 0.494081 * Train accuracy / confusion: 81.25% / [[290, 71], [79, 360]], * Val accuracy / confusion: 72.69% / [[159, 71], [71, 219]] ------------------------------ Epoch 383 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.442015 - Iter 024 / 025, Loss: 0.548625 * Train accuracy / confusion: 82.25% / [[279, 81], [61, 379]], * Val accuracy / confusion: 72.31% / [[146, 84], [60, 230]] ------------------------------ Epoch 384 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.309091 - Iter 024 / 025, Loss: 0.479926 * Train accuracy / confusion: 82.50% / [[283, 76], [64, 377]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 385 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.260311 - Iter 024 / 025, Loss: 0.389347 * Train accuracy / confusion: 80.50% / [[277, 76], [80, 367]], * Val accuracy / confusion: 69.62% / [[150, 80], [78, 212]] ------------------------------ Epoch 386 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.521049 - Iter 024 / 025, Loss: 0.353546 * Train accuracy / confusion: 80.38% / [[276, 80], [77, 367]], * Val accuracy / confusion: 71.15% / [[152, 78], [72, 218]] ------------------------------ Epoch 387 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.447822 - Iter 024 / 025, Loss: 0.315794 * Train accuracy / confusion: 81.50% / [[277, 80], [68, 375]], * Val accuracy / confusion: 72.12% / [[143, 87], [58, 232]] ------------------------------ Epoch 388 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.428195 - Iter 024 / 025, Loss: 0.355143 * Train accuracy / confusion: 80.00% / [[267, 87], [73, 373]], * Val accuracy / confusion: 70.00% / [[146, 84], [72, 218]] ------------------------------ Epoch 389 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430064 - Iter 024 / 025, Loss: 0.413850 * Train accuracy / confusion: 79.00% / [[260, 90], [78, 372]], * Val accuracy / confusion: 70.58% / [[150, 80], [73, 217]] ------------------------------ Epoch 390 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390119 - Iter 024 / 025, Loss: 0.520476 * Train accuracy / confusion: 81.00% / [[272, 79], [73, 376]], * Val accuracy / confusion: 70.96% / [[140, 90], [61, 229]] ------------------------------ Epoch 391 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.428223 - Iter 024 / 025, Loss: 0.333729 * Train accuracy / confusion: 79.50% / [[265, 90], [74, 371]], * Val accuracy / confusion: 71.54% / [[149, 81], [67, 223]] ------------------------------ Epoch 392 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.463850 - Iter 024 / 025, Loss: 0.505984 * Train accuracy / confusion: 80.25% / [[270, 87], [71, 372]], * Val accuracy / confusion: 71.35% / [[137, 93], [56, 234]] ------------------------------ Epoch 393 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.480307 - Iter 024 / 025, Loss: 0.383993 * Train accuracy / confusion: 82.38% / [[278, 79], [62, 381]], * Val accuracy / confusion: 71.73% / [[156, 74], [73, 217]] ------------------------------ Epoch 394 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.437858 - Iter 024 / 025, Loss: 0.454428 * Train accuracy / confusion: 80.75% / [[270, 87], [67, 376]], * Val accuracy / confusion: 72.50% / [[151, 79], [64, 226]] ------------------------------ Epoch 395 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.362258 - Iter 024 / 025, Loss: 0.453174 * Train accuracy / confusion: 81.00% / [[275, 81], [71, 373]], * Val accuracy / confusion: 69.23% / [[145, 85], [75, 215]] ------------------------------ Epoch 396 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.570624 - Iter 024 / 025, Loss: 0.513548 * Train accuracy / confusion: 82.12% / [[278, 76], [67, 379]], * Val accuracy / confusion: 70.19% / [[146, 84], [71, 219]] ------------------------------ Epoch 397 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.338486 - Iter 024 / 025, Loss: 0.770940 * Train accuracy / confusion: 79.62% / [[275, 85], [78, 362]], * Val accuracy / confusion: 72.69% / [[148, 82], [60, 230]] ------------------------------ Epoch 398 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.358910 - Iter 024 / 025, Loss: 0.567152 * Train accuracy / confusion: 80.62% / [[270, 88], [67, 375]], * Val accuracy / confusion: 71.15% / [[147, 83], [67, 223]] ------------------------------ Epoch 399 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.507770 - Iter 024 / 025, Loss: 0.359420 * Train accuracy / confusion: 78.38% / [[268, 87], [86, 359]], * Val accuracy / confusion: 73.27% / [[167, 63], [76, 214]] ------------------------------ Epoch 400 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.281565 - Iter 024 / 025, Loss: 0.313794 * Train accuracy / confusion: 81.75% / [[270, 88], [58, 384]], * Val accuracy / confusion: 71.92% / [[155, 75], [71, 219]] ------------------------------ Epoch 401 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.289060 - Iter 024 / 025, Loss: 0.323070 * Train accuracy / confusion: 80.88% / [[280, 81], [72, 367]], * Val accuracy / confusion: 70.77% / [[145, 85], [67, 223]] ------------------------------ Epoch 402 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.301345 - Iter 024 / 025, Loss: 0.255601 * Train accuracy / confusion: 81.62% / [[279, 77], [70, 374]], * Val accuracy / confusion: 70.77% / [[146, 84], [68, 222]] ------------------------------ Epoch 403 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.517413 - Iter 024 / 025, Loss: 0.281159 * Train accuracy / confusion: 80.25% / [[273, 81], [77, 369]], * Val accuracy / confusion: 69.81% / [[149, 81], [76, 214]] ------------------------------ Epoch 404 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.389515 - Iter 024 / 025, Loss: 0.365379 * Train accuracy / confusion: 80.62% / [[278, 77], [78, 367]], * Val accuracy / confusion: 69.42% / [[144, 86], [73, 217]] ------------------------------ Epoch 405 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.305217 - Iter 024 / 025, Loss: 0.501279 * Train accuracy / confusion: 80.12% / [[264, 88], [71, 377]], * Val accuracy / confusion: 71.73% / [[146, 84], [63, 227]] ------------------------------ Epoch 406 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.249863 - Iter 024 / 025, Loss: 0.451391 * Train accuracy / confusion: 83.50% / [[284, 69], [63, 384]], * Val accuracy / confusion: 72.69% / [[158, 72], [70, 220]] ------------------------------ Epoch 407 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.315768 - Iter 024 / 025, Loss: 0.439313 * Train accuracy / confusion: 79.75% / [[266, 85], [77, 372]], * Val accuracy / confusion: 71.15% / [[160, 70], [80, 210]] ------------------------------ Epoch 408 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.474939 - Iter 024 / 025, Loss: 0.472864 * Train accuracy / confusion: 81.00% / [[267, 90], [62, 381]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 409 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.379140 - Iter 024 / 025, Loss: 0.480968 * Train accuracy / confusion: 81.75% / [[276, 77], [69, 378]], * Val accuracy / confusion: 71.73% / [[150, 80], [67, 223]] ------------------------------ Epoch 410 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.330488 - Iter 024 / 025, Loss: 0.476634 * Train accuracy / confusion: 80.00% / [[272, 85], [75, 368]], * Val accuracy / confusion: 70.38% / [[153, 77], [77, 213]] ------------------------------ Epoch 411 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.388980 - Iter 024 / 025, Loss: 0.491315 * Train accuracy / confusion: 82.12% / [[276, 77], [66, 381]], * Val accuracy / confusion: 70.00% / [[144, 86], [70, 220]] ------------------------------ Epoch 412 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.289353 - Iter 024 / 025, Loss: 0.379373 * Train accuracy / confusion: 79.50% / [[269, 88], [76, 367]], * Val accuracy / confusion: 70.58% / [[152, 78], [75, 215]] ------------------------------ Epoch 413 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.329833 - Iter 024 / 025, Loss: 0.474376 * Train accuracy / confusion: 81.25% / [[274, 82], [68, 376]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 414 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.340789 - Iter 024 / 025, Loss: 0.364479 * Train accuracy / confusion: 82.00% / [[283, 75], [69, 373]], * Val accuracy / confusion: 69.81% / [[145, 85], [72, 218]] ------------------------------ Epoch 415 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.424854 - Iter 024 / 025, Loss: 0.508491 * Train accuracy / confusion: 81.75% / [[282, 75], [71, 372]], * Val accuracy / confusion: 71.54% / [[149, 81], [67, 223]] ------------------------------ Epoch 416 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.296820 - Iter 024 / 025, Loss: 0.284754 * Train accuracy / confusion: 81.50% / [[281, 80], [68, 371]], * Val accuracy / confusion: 68.65% / [[147, 83], [80, 210]] ------------------------------ Epoch 417 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.403626 - Iter 024 / 025, Loss: 0.398792 * Train accuracy / confusion: 79.50% / [[273, 84], [80, 363]], * Val accuracy / confusion: 70.00% / [[151, 79], [77, 213]] ------------------------------ Epoch 418 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.414188 - Iter 024 / 025, Loss: 0.384093 * Train accuracy / confusion: 81.12% / [[280, 76], [75, 369]], * Val accuracy / confusion: 70.96% / [[140, 90], [61, 229]] ------------------------------ Epoch 419 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.533959 - Iter 024 / 025, Loss: 0.415979 * Train accuracy / confusion: 82.62% / [[280, 74], [65, 381]], * Val accuracy / confusion: 70.00% / [[147, 83], [73, 217]] ------------------------------ Epoch 420 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.407307 - Iter 024 / 025, Loss: 0.433200 * Train accuracy / confusion: 81.38% / [[271, 84], [65, 380]], * Val accuracy / confusion: 70.19% / [[150, 80], [75, 215]] ------------------------------ Epoch 421 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.444978 - Iter 024 / 025, Loss: 0.401209 * Train accuracy / confusion: 80.88% / [[281, 77], [76, 366]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 422 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.437187 - Iter 024 / 025, Loss: 0.312142 * Train accuracy / confusion: 81.88% / [[280, 75], [70, 375]], * Val accuracy / confusion: 69.81% / [[144, 86], [71, 219]] ------------------------------ Epoch 423 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.328234 - Iter 024 / 025, Loss: 0.415085 * Train accuracy / confusion: 80.62% / [[280, 76], [79, 365]], * Val accuracy / confusion: 73.27% / [[156, 74], [65, 225]] ------------------------------ Epoch 424 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.538698 - Iter 024 / 025, Loss: 0.408564 * Train accuracy / confusion: 80.62% / [[272, 80], [75, 373]], * Val accuracy / confusion: 70.19% / [[142, 88], [67, 223]] ------------------------------ Epoch 425 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.478998 - Iter 024 / 025, Loss: 0.475018 * Train accuracy / confusion: 78.88% / [[273, 85], [84, 358]], * Val accuracy / confusion: 71.54% / [[150, 80], [68, 222]] ------------------------------ Epoch 426 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.314144 - Iter 024 / 025, Loss: 0.556397 * Train accuracy / confusion: 80.12% / [[282, 77], [82, 359]], * Val accuracy / confusion: 70.00% / [[149, 81], [75, 215]] ------------------------------ Epoch 427 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.545462 - Iter 024 / 025, Loss: 0.564507 * Train accuracy / confusion: 80.50% / [[274, 81], [75, 370]], * Val accuracy / confusion: 72.31% / [[160, 70], [74, 216]] ------------------------------ Epoch 428 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.383643 - Iter 024 / 025, Loss: 0.316228 * Train accuracy / confusion: 80.00% / [[264, 88], [72, 376]], * Val accuracy / confusion: 71.54% / [[152, 78], [70, 220]] ------------------------------ Epoch 429 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.426379 - Iter 024 / 025, Loss: 0.282061 * Train accuracy / confusion: 80.62% / [[273, 80], [75, 372]], * Val accuracy / confusion: 70.38% / [[145, 85], [69, 221]] ------------------------------ Epoch 430 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.581665 - Iter 024 / 025, Loss: 0.464739 * Train accuracy / confusion: 82.62% / [[278, 79], [60, 383]], * Val accuracy / confusion: 73.65% / [[157, 73], [64, 226]] ------------------------------ Epoch 431 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.397651 - Iter 024 / 025, Loss: 0.686076 * Train accuracy / confusion: 80.12% / [[274, 77], [82, 367]], * Val accuracy / confusion: 70.77% / [[143, 87], [65, 225]] ------------------------------ Epoch 432 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.308611 - Iter 024 / 025, Loss: 0.748392 * Train accuracy / confusion: 79.25% / [[269, 87], [79, 365]], * Val accuracy / confusion: 71.35% / [[149, 81], [68, 222]] ------------------------------ Epoch 433 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.270671 - Iter 024 / 025, Loss: 0.389381 * Train accuracy / confusion: 82.62% / [[274, 76], [63, 387]], * Val accuracy / confusion: 71.92% / [[162, 68], [78, 212]] ------------------------------ Epoch 434 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.457110 - Iter 024 / 025, Loss: 0.498461 * Train accuracy / confusion: 81.00% / [[278, 79], [73, 370]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 435 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.378174 - Iter 024 / 025, Loss: 0.379466 * Train accuracy / confusion: 81.12% / [[279, 78], [73, 370]], * Val accuracy / confusion: 70.19% / [[147, 83], [72, 218]] ------------------------------ Epoch 436 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.416695 - Iter 024 / 025, Loss: 0.205632 * Train accuracy / confusion: 79.88% / [[273, 86], [75, 366]], * Val accuracy / confusion: 71.15% / [[156, 74], [76, 214]] ------------------------------ Epoch 437 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.372857 - Iter 024 / 025, Loss: 0.393642 * Train accuracy / confusion: 81.88% / [[279, 76], [69, 376]], * Val accuracy / confusion: 71.92% / [[146, 84], [62, 228]] ------------------------------ Epoch 438 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.521838 - Iter 024 / 025, Loss: 0.528497 * Train accuracy / confusion: 80.75% / [[271, 81], [73, 375]], * Val accuracy / confusion: 72.12% / [[160, 70], [75, 215]] ------------------------------ Epoch 439 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.388935 - Iter 024 / 025, Loss: 0.495761 * Train accuracy / confusion: 81.38% / [[272, 83], [66, 379]], * Val accuracy / confusion: 70.38% / [[147, 83], [71, 219]] ------------------------------ Epoch 440 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.446445 - Iter 024 / 025, Loss: 0.374359 * Train accuracy / confusion: 78.88% / [[262, 91], [78, 369]], * Val accuracy / confusion: 70.19% / [[142, 88], [67, 223]] ------------------------------ Epoch 441 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.611342 - Iter 024 / 025, Loss: 0.422998 * Train accuracy / confusion: 80.62% / [[265, 90], [65, 380]], * Val accuracy / confusion: 73.65% / [[164, 66], [71, 219]] ------------------------------ Epoch 442 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.513020 - Iter 024 / 025, Loss: 0.401772 * Train accuracy / confusion: 79.00% / [[264, 88], [80, 368]], * Val accuracy / confusion: 72.50% / [[152, 78], [65, 225]] ------------------------------ Epoch 443 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.548315 - Iter 024 / 025, Loss: 0.439009 * Train accuracy / confusion: 81.50% / [[284, 71], [77, 368]], * Val accuracy / confusion: 73.08% / [[159, 71], [69, 221]] ------------------------------ Epoch 444 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.653447 - Iter 024 / 025, Loss: 0.409196 * Train accuracy / confusion: 82.00% / [[284, 74], [70, 372]], * Val accuracy / confusion: 68.65% / [[146, 84], [79, 211]] ------------------------------ Epoch 445 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.374190 - Iter 024 / 025, Loss: 0.460529 * Train accuracy / confusion: 81.12% / [[279, 78], [73, 370]], * Val accuracy / confusion: 71.54% / [[146, 84], [64, 226]] ------------------------------ Epoch 446 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.339123 - Iter 024 / 025, Loss: 0.372773 * Train accuracy / confusion: 79.50% / [[274, 85], [79, 362]], * Val accuracy / confusion: 69.23% / [[145, 85], [75, 215]] ------------------------------ Epoch 447 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.376338 - Iter 024 / 025, Loss: 0.357766 * Train accuracy / confusion: 80.38% / [[278, 78], [79, 365]], * Val accuracy / confusion: 70.58% / [[148, 82], [71, 219]] ------------------------------ Epoch 448 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.487143 - Iter 024 / 025, Loss: 0.485751 * Train accuracy / confusion: 79.00% / [[265, 91], [77, 367]], * Val accuracy / confusion: 73.27% / [[154, 76], [63, 227]] ------------------------------ Epoch 449 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.327457 - Iter 024 / 025, Loss: 0.574287 * Train accuracy / confusion: 79.25% / [[266, 88], [78, 368]], * Val accuracy / confusion: 67.12% / [[135, 95], [76, 214]] ------------------------------ Epoch 450 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.348343 - Iter 024 / 025, Loss: 0.604357 * Train accuracy / confusion: 82.38% / [[286, 71], [70, 373]], * Val accuracy / confusion: 69.81% / [[146, 84], [73, 217]] ------------------------------ Epoch 451 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.405895 - Iter 024 / 025, Loss: 0.549229 * Train accuracy / confusion: 80.12% / [[274, 84], [75, 367]], * Val accuracy / confusion: 72.88% / [[151, 79], [62, 228]] ------------------------------ Epoch 452 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.381468 - Iter 024 / 025, Loss: 0.557862 * Train accuracy / confusion: 79.88% / [[269, 93], [68, 370]], * Val accuracy / confusion: 70.77% / [[151, 79], [73, 217]] ------------------------------ Epoch 453 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.525041 - Iter 024 / 025, Loss: 0.364701 * Train accuracy / confusion: 81.12% / [[279, 80], [71, 370]], * Val accuracy / confusion: 73.46% / [[154, 76], [62, 228]] ------------------------------ Epoch 454 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.306646 - Iter 024 / 025, Loss: 0.474600 * Train accuracy / confusion: 79.38% / [[274, 85], [80, 361]], * Val accuracy / confusion: 71.35% / [[145, 85], [64, 226]] ------------------------------ Epoch 455 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.394946 - Iter 024 / 025, Loss: 0.387034 * Train accuracy / confusion: 81.88% / [[281, 77], [68, 374]], * Val accuracy / confusion: 71.15% / [[154, 76], [74, 216]] ------------------------------ Epoch 456 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.539515 - Iter 024 / 025, Loss: 0.439842 * Train accuracy / confusion: 79.62% / [[265, 91], [72, 372]], * Val accuracy / confusion: 71.92% / [[155, 75], [71, 219]] ------------------------------ Epoch 457 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.463216 - Iter 024 / 025, Loss: 0.302215 * Train accuracy / confusion: 82.88% / [[282, 73], [64, 381]], * Val accuracy / confusion: 71.15% / [[155, 75], [75, 215]] ------------------------------ Epoch 458 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.417509 - Iter 024 / 025, Loss: 0.430043 * Train accuracy / confusion: 79.88% / [[272, 80], [81, 367]], * Val accuracy / confusion: 72.69% / [[158, 72], [70, 220]] ------------------------------ Epoch 459 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.513497 - Iter 024 / 025, Loss: 0.375700 * Train accuracy / confusion: 79.38% / [[264, 92], [73, 371]], * Val accuracy / confusion: 70.58% / [[147, 83], [70, 220]] ------------------------------ Epoch 460 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.476457 - Iter 024 / 025, Loss: 0.309346 * Train accuracy / confusion: 81.00% / [[275, 81], [71, 373]], * Val accuracy / confusion: 71.35% / [[145, 85], [64, 226]] ------------------------------ Epoch 461 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408401 - Iter 024 / 025, Loss: 0.360786 * Train accuracy / confusion: 82.25% / [[278, 75], [67, 380]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 462 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.285212 - Iter 024 / 025, Loss: 0.362067 * Train accuracy / confusion: 81.88% / [[273, 81], [64, 382]], * Val accuracy / confusion: 70.19% / [[150, 80], [75, 215]] ------------------------------ Epoch 463 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.438621 - Iter 024 / 025, Loss: 0.321584 * Train accuracy / confusion: 82.12% / [[275, 82], [61, 382]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 464 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.470100 - Iter 024 / 025, Loss: 0.460853 * Train accuracy / confusion: 79.38% / [[275, 84], [81, 360]], * Val accuracy / confusion: 69.81% / [[149, 81], [76, 214]] ------------------------------ Epoch 465 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.368799 - Iter 024 / 025, Loss: 0.524964 * Train accuracy / confusion: 79.88% / [[271, 89], [72, 368]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 466 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.353456 - Iter 024 / 025, Loss: 0.305175 * Train accuracy / confusion: 82.00% / [[286, 76], [68, 370]], * Val accuracy / confusion: 68.85% / [[134, 96], [66, 224]] ------------------------------ Epoch 467 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.479301 - Iter 024 / 025, Loss: 0.728087 * Train accuracy / confusion: 80.38% / [[273, 85], [72, 370]], * Val accuracy / confusion: 70.00% / [[138, 92], [64, 226]] ------------------------------ Epoch 468 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.365427 - Iter 024 / 025, Loss: 0.360087 * Train accuracy / confusion: 82.50% / [[284, 77], [63, 376]], * Val accuracy / confusion: 73.08% / [[157, 73], [67, 223]] ------------------------------ Epoch 469 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.469494 - Iter 024 / 025, Loss: 0.480517 * Train accuracy / confusion: 80.62% / [[277, 79], [76, 368]], * Val accuracy / confusion: 72.12% / [[164, 66], [79, 211]] ------------------------------ Epoch 470 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.328603 - Iter 024 / 025, Loss: 0.376733 * Train accuracy / confusion: 81.25% / [[270, 78], [72, 380]], * Val accuracy / confusion: 71.35% / [[151, 79], [70, 220]] ------------------------------ Epoch 471 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.553194 - Iter 024 / 025, Loss: 0.617817 * Train accuracy / confusion: 79.50% / [[269, 89], [75, 367]], * Val accuracy / confusion: 70.58% / [[144, 86], [67, 223]] ------------------------------ Epoch 472 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.440964 - Iter 024 / 025, Loss: 0.625196 * Train accuracy / confusion: 82.00% / [[281, 72], [72, 375]], * Val accuracy / confusion: 70.58% / [[147, 83], [70, 220]] ------------------------------ Epoch 473 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.402849 - Iter 024 / 025, Loss: 0.334549 * Train accuracy / confusion: 81.12% / [[280, 80], [71, 369]], * Val accuracy / confusion: 71.92% / [[152, 78], [68, 222]] ------------------------------ Epoch 474 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.413949 - Iter 024 / 025, Loss: 0.414863 * Train accuracy / confusion: 82.25% / [[284, 73], [69, 374]], * Val accuracy / confusion: 71.35% / [[156, 74], [75, 215]] ------------------------------ Epoch 475 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.472040 - Iter 024 / 025, Loss: 0.326776 * Train accuracy / confusion: 82.25% / [[276, 75], [67, 382]], * Val accuracy / confusion: 70.77% / [[153, 77], [75, 215]] ------------------------------ Epoch 476 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.437949 - Iter 024 / 025, Loss: 0.456984 * Train accuracy / confusion: 81.38% / [[277, 80], [69, 374]], * Val accuracy / confusion: 70.58% / [[148, 82], [71, 219]] ------------------------------ Epoch 477 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.404199 - Iter 024 / 025, Loss: 0.400555 * Train accuracy / confusion: 81.12% / [[272, 80], [71, 377]], * Val accuracy / confusion: 73.65% / [[151, 79], [58, 232]] ------------------------------ Epoch 478 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.472111 - Iter 024 / 025, Loss: 0.232574 * Train accuracy / confusion: 81.62% / [[273, 85], [62, 380]], * Val accuracy / confusion: 72.12% / [[158, 72], [73, 217]] ------------------------------ Epoch 479 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.438844 - Iter 024 / 025, Loss: 0.551827 * Train accuracy / confusion: 82.25% / [[281, 74], [68, 377]], * Val accuracy / confusion: 70.00% / [[152, 78], [78, 212]] ------------------------------ Epoch 480 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.400512 - Iter 024 / 025, Loss: 0.171234 * Train accuracy / confusion: 81.50% / [[273, 81], [67, 379]], * Val accuracy / confusion: 72.12% / [[154, 76], [69, 221]] ------------------------------ Epoch 481 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.450290 - Iter 024 / 025, Loss: 0.484751 * Train accuracy / confusion: 81.12% / [[276, 78], [73, 373]], * Val accuracy / confusion: 71.35% / [[154, 76], [73, 217]] ------------------------------ Epoch 482 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.288144 - Iter 024 / 025, Loss: 0.377760 * Train accuracy / confusion: 81.12% / [[282, 78], [73, 367]], * Val accuracy / confusion: 71.35% / [[146, 84], [65, 225]] ------------------------------ Epoch 483 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.325661 - Iter 024 / 025, Loss: 0.497028 * Train accuracy / confusion: 82.50% / [[283, 73], [67, 377]], * Val accuracy / confusion: 69.04% / [[146, 84], [77, 213]] ------------------------------ Epoch 484 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.606336 - Iter 024 / 025, Loss: 0.377087 * Train accuracy / confusion: 81.38% / [[272, 81], [68, 379]], * Val accuracy / confusion: 69.81% / [[137, 93], [64, 226]] ------------------------------ Epoch 485 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.561108 - Iter 024 / 025, Loss: 0.445170 * Train accuracy / confusion: 81.00% / [[273, 86], [66, 375]], * Val accuracy / confusion: 71.73% / [[151, 79], [68, 222]] ------------------------------ Epoch 486 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.592165 - Iter 024 / 025, Loss: 0.435217 * Train accuracy / confusion: 80.88% / [[276, 81], [72, 371]], * Val accuracy / confusion: 69.42% / [[149, 81], [78, 212]] ------------------------------ Epoch 487 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.515818 - Iter 024 / 025, Loss: 0.520324 * Train accuracy / confusion: 82.00% / [[285, 68], [76, 371]], * Val accuracy / confusion: 70.38% / [[151, 79], [75, 215]] ------------------------------ Epoch 488 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.406771 - Iter 024 / 025, Loss: 0.397963 * Train accuracy / confusion: 80.25% / [[270, 83], [75, 372]], * Val accuracy / confusion: 70.58% / [[135, 95], [58, 232]] ------------------------------ Epoch 489 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.382377 - Iter 024 / 025, Loss: 0.495741 * Train accuracy / confusion: 81.75% / [[281, 74], [72, 373]], * Val accuracy / confusion: 71.54% / [[149, 81], [67, 223]] ------------------------------ Epoch 490 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.490869 - Iter 024 / 025, Loss: 0.444840 * Train accuracy / confusion: 80.25% / [[271, 82], [76, 371]], * Val accuracy / confusion: 67.88% / [[153, 77], [90, 200]] ------------------------------ Epoch 491 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.322325 - Iter 024 / 025, Loss: 0.346971 * Train accuracy / confusion: 80.12% / [[271, 87], [72, 370]], * Val accuracy / confusion: 70.77% / [[143, 87], [65, 225]] ------------------------------ Epoch 492 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.439835 - Iter 024 / 025, Loss: 0.400642 * Train accuracy / confusion: 79.50% / [[267, 90], [74, 369]], * Val accuracy / confusion: 69.23% / [[150, 80], [80, 210]] ------------------------------ Epoch 493 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.400505 - Iter 024 / 025, Loss: 0.431358 * Train accuracy / confusion: 80.25% / [[270, 87], [71, 372]], * Val accuracy / confusion: 71.73% / [[156, 74], [73, 217]] ------------------------------ Epoch 494 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.428505 - Iter 024 / 025, Loss: 0.400678 * Train accuracy / confusion: 80.50% / [[269, 86], [70, 375]], * Val accuracy / confusion: 69.23% / [[145, 85], [75, 215]] ------------------------------ Epoch 495 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.309089 - Iter 024 / 025, Loss: 0.630347 * Train accuracy / confusion: 81.00% / [[271, 85], [67, 377]], * Val accuracy / confusion: 71.54% / [[153, 77], [71, 219]] ------------------------------ Epoch 496 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.358036 - Iter 024 / 025, Loss: 0.504788 * Train accuracy / confusion: 80.25% / [[274, 87], [71, 368]], * Val accuracy / confusion: 70.96% / [[145, 85], [66, 224]] ------------------------------ Epoch 497 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342355 - Iter 024 / 025, Loss: 0.477139 * Train accuracy / confusion: 80.88% / [[265, 84], [69, 382]], * Val accuracy / confusion: 70.19% / [[152, 78], [77, 213]] ------------------------------ Epoch 498 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.403708 - Iter 024 / 025, Loss: 0.652973 * Train accuracy / confusion: 80.38% / [[275, 82], [75, 368]], * Val accuracy / confusion: 72.88% / [[161, 69], [72, 218]] ------------------------------ Epoch 499 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.283076 - Iter 024 / 025, Loss: 0.319960 * Train accuracy / confusion: 81.00% / [[275, 80], [72, 373]], * Val accuracy / confusion: 69.42% / [[154, 76], [83, 207]] ------------------------------ Epoch 500 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.375607 - Iter 024 / 025, Loss: 0.338723 * Train accuracy / confusion: 78.75% / [[268, 89], [81, 362]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 74.20% - Confusion matrix (last model): [[1000 410] [ 395 1315]]
- Test accuracy (best model): 70.29% - Confusion matrix (best model): [[1015 395] [ 532 1178]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyCNN_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '00299': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '00671212_160819'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
'00176': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00602435_270217'},
'00591': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00896386_240914'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00811': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '01116389_271118'},
'01235': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01336270_040717'},
'00835': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01134450_140519'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'00719': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01006707_260319'},
'00495': {'GT': 1, 'Acc': ' 60.00%', 'Pred': [12, 18], 'edfname': '00805584_090819'},
'00862': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01139924_300315'},
'00913': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01151967_160414'},
'00097': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00372136_181214'},
'00122': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00416942_190516'},
'00439': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00760780_141118'},
'01378': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01432133_160519'},
'00705': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00986061_270116'},
'00212': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00617893_231018'},
'01105': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01266696_110516'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'00531': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00840844_250119'},
'00192': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '00608961_131118'},
'00643': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00948785_120116'},
'01177': {'GT': 1, 'Acc': ' 40.00%', 'Pred': [18, 12], 'edfname': '01300390_251116'},
'01209': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01318352_281118'},
'00341': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695058_191017'},
'00357': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00707209_261219'},
'00527': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00840062_080519'},
'01307': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '01376302_060718'},
'00058': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '00285244_020414'},
'00124': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00418981_060116'},
'00508': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00817022_010415'},
'00021': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00141670_081217'},
'00408': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '00740750_110315'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'01330': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01392885_240718'},
'00329': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '00685248_150414'},
'00277': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00657017_281218'},
'00900': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01147100'},
'00700': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00985401_011117'},
'00584': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '00891889_060717'},
'01066': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01242983_071215'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00369252_131216'},
'01165': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01296533_281116'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00030': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_230317'},
'01123': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01276165_040117'},
'00982': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01200248_290120'},
'00917': {'GT': 0, 'Acc': ' 33.33%', 'Pred': [10, 20], 'edfname': '01154159_230414'},
'00255': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '00645911_021115'},
'01039': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01235034_290120'},
'00961': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01182545_070316'},
'00338': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00692685_200919'},
'00346': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '00698358_020916'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'00704': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_240215'},
'00125': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00418981_090316'},
'00859': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01139924_060417'},
'00471': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00784417_100315'},
'00498': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00809366_050116'},
'01239': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01338557_190717'},
'00481': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00796686_020819'},
'00369': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '00715828_111016'},
'01281': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '01358607_280918'},
'01360': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01415643_150119'},
'01288': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01364379_260919'},
'00885': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '01142810_180214'},
'00858': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139894_140214'},
'01138': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '01281605_070716'},
'00821': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01128393_300715'},
'00870': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01139947_120214'},
'01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00464': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00779318_101117'},
'00923': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '01155730_070514'},
'00815': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01125477_030918'},
'01287': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01364379_230118'},
'01160': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01295899_041016'},
'00104': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '00395714_170915'},
'01353': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01410438_241218'},
'01267': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01351393_111119'},
'01156': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01293646_120719'},
'00504': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00813343_041218'},
'01045': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01235281_191015'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00094': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00366974_061118'},
'00741': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01025734_280715'},
'00303': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00672867_031116'},
'00156': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00502785_041019'},
'00851': {'GT': 0, 'Acc': ' 36.67%', 'Pred': [11, 19], 'edfname': '01138297_230114'},
'00730': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01011922_270815'},
'00343': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00695272_100519'},
'00756': {'GT': 1, 'Acc': ' 66.67%', 'Pred': [10, 20], 'edfname': '01035162_180119'},
'01232': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01335435_121119'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00076': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00317645_311016'},
'00653': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00952170_060516'}}
class M5(nn.Module):
def __init__(self, n_input=20, n_output=3, stride=4, n_channel=256,
use_age=True, final_pool='average'):
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.use_age = use_age
self.conv1 = nn.Conv1d(n_input, n_channel, kernel_size=41, stride=2)
self.bn1 = nn.BatchNorm1d(n_channel)
self.pool1 = nn.MaxPool1d(2)
self.conv2 = nn.Conv1d(n_channel, n_channel, kernel_size=11)
self.bn2 = nn.BatchNorm1d(n_channel)
self.pool2 = nn.MaxPool1d(2)
self.conv3 = nn.Conv1d(n_channel, 2 * n_channel, kernel_size=11)
self.bn3 = nn.BatchNorm1d(2 * n_channel)
self.pool3 = nn.MaxPool1d(2)
self.conv4 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
self.bn4 = nn.BatchNorm1d(2 * n_channel)
self.pool4 = nn.MaxPool1d(2)
self.conv5 = nn.Conv1d(2 * n_channel, 2 * n_channel, kernel_size=11)
self.bn5 = nn.BatchNorm1d(2 * n_channel)
self.pool5 = nn.MaxPool1d(2)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
if self.use_age:
self.fc1 = nn.Linear(2 * n_channel + 1, 2 * n_channel)
else:
self.fc1 = nn.Linear(2 * n_channel, 2 * n_channel)
self.dropout = nn.Dropout(p=0.3)
self.bnfc1 = nn.BatchNorm1d(2 * n_channel)
self.fc2 = nn.Linear(2 * n_channel, n_output)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def forward(self, x, age, print_shape=False):
# conv-bn-relu-pool
x = self.conv1(x)
x = F.relu(self.bn1(x))
x = self.pool1(x)
x = self.conv2(x)
x = F.relu(self.bn2(x))
x = self.pool2(x)
x = self.conv3(x)
x = F.relu(self.bn3(x))
x = self.pool3(x)
x = self.conv4(x)
x = F.relu(self.bn4(x))
x = self.pool4(x)
x = self.conv5(x)
x = F.relu(self.bn5(x))
x = self.pool5(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
# fc-bn-dropout-relu-fc
x = self.fc1(x)
x = self.bnfc1(x)
x = self.dropout(x)
x = F.relu(x)
x = self.fc2(x)
return x
# return F.log_softmax(x, dim=1)
model = M5(n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'M5-like')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
M5( (conv1): Conv1d(20, 256, kernel_size=(41,), stride=(2,)) (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool1): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv2): Conv1d(256, 256, kernel_size=(11,), stride=(1,)) (bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool2): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv3): Conv1d(256, 512, kernel_size=(11,), stride=(1,)) (bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool3): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv4): Conv1d(512, 512, kernel_size=(11,), stride=(1,)) (bn4): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool4): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (conv5): Conv1d(512, 512, kernel_size=(11,), stride=(1,)) (bn5): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (pool5): MaxPool1d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) (final_pool): AdaptiveMaxPool1d(output_size=1) (fc1): Linear(in_features=513, out_features=512, bias=True) (dropout): Dropout(p=0.3, inplace=False) (bnfc1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (fc2): Linear(in_features=512, out_features=2, bias=True) ) Shape right before squeezing: torch.Size([32, 512, 21]) The Number of parameters of the model: 8,411,138
# record = learning_rate_search(model,
# min_log_lr=-4.5,
# max_log_lr=-1.4,
# trials=300,
# epochs=1)
# draw_learning_rate_record(record)
# best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
best_log_lr = -3.0
print('best_log_lr:', best_log_lr)
best_log_lr: -3.0
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.716904 - Iter 024 / 025, Loss: 0.729847 * Train accuracy / confusion: 51.75% / [[134, 224], [162, 280]], * Val accuracy / confusion: 50.19% / [[178, 52], [207, 83]] ------------------------------ Epoch 002 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.597452 - Iter 024 / 025, Loss: 0.722174 * Train accuracy / confusion: 58.12% / [[156, 205], [130, 309]], * Val accuracy / confusion: 60.96% / [[96, 134], [69, 221]] ------------------------------ Epoch 003 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.640145 - Iter 024 / 025, Loss: 0.671307 * Train accuracy / confusion: 60.38% / [[176, 181], [136, 307]], * Val accuracy / confusion: 61.35% / [[57, 173], [28, 262]] ------------------------------ Epoch 004 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.581339 - Iter 024 / 025, Loss: 0.647592 * Train accuracy / confusion: 63.25% / [[179, 175], [119, 327]], * Val accuracy / confusion: 66.35% / [[87, 143], [32, 258]] ------------------------------ Epoch 005 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.650148 - Iter 024 / 025, Loss: 0.738641 * Train accuracy / confusion: 66.75% / [[196, 154], [112, 338]], * Val accuracy / confusion: 64.62% / [[91, 139], [45, 245]] ------------------------------ Epoch 006 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.619706 - Iter 024 / 025, Loss: 0.620428 * Train accuracy / confusion: 63.25% / [[170, 186], [108, 336]], * Val accuracy / confusion: 67.88% / [[129, 101], [66, 224]] ------------------------------ Epoch 007 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.635427 - Iter 024 / 025, Loss: 0.629057 * Train accuracy / confusion: 66.00% / [[181, 176], [96, 347]], * Val accuracy / confusion: 58.08% / [[211, 19], [199, 91]] ------------------------------ Epoch 008 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.539760 - Iter 024 / 025, Loss: 0.693231 * Train accuracy / confusion: 65.38% / [[211, 149], [128, 312]], * Val accuracy / confusion: 63.08% / [[48, 182], [10, 280]] ------------------------------ Epoch 009 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.509633 - Iter 024 / 025, Loss: 0.572460 * Train accuracy / confusion: 68.12% / [[193, 159], [96, 352]], * Val accuracy / confusion: 64.42% / [[60, 170], [15, 275]] ------------------------------ Epoch 010 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.514840 - Iter 024 / 025, Loss: 0.528263 * Train accuracy / confusion: 69.38% / [[230, 129], [116, 325]], * Val accuracy / confusion: 68.85% / [[116, 114], [48, 242]] ------------------------------ Epoch 011 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.619370 - Iter 024 / 025, Loss: 0.608214 * Train accuracy / confusion: 66.38% / [[202, 157], [112, 329]], * Val accuracy / confusion: 68.08% / [[96, 134], [32, 258]] ------------------------------ Epoch 012 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.579483 - Iter 024 / 025, Loss: 0.629287 * Train accuracy / confusion: 68.88% / [[217, 140], [109, 334]], * Val accuracy / confusion: 65.19% / [[198, 32], [149, 141]] ------------------------------ Epoch 013 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.568886 - Iter 024 / 025, Loss: 0.553802 * Train accuracy / confusion: 70.25% / [[229, 125], [113, 333]], * Val accuracy / confusion: 72.50% / [[164, 66], [77, 213]] ------------------------------ Epoch 014 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.632754 - Iter 024 / 025, Loss: 0.674687 * Train accuracy / confusion: 67.00% / [[212, 146], [118, 324]], * Val accuracy / confusion: 67.50% / [[91, 139], [30, 260]] ------------------------------ Epoch 015 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.620588 - Iter 024 / 025, Loss: 0.564164 * Train accuracy / confusion: 69.88% / [[216, 138], [103, 343]], * Val accuracy / confusion: 72.69% / [[134, 96], [46, 244]] ------------------------------ Epoch 016 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.833467 - Iter 024 / 025, Loss: 0.518583 * Train accuracy / confusion: 67.25% / [[200, 155], [107, 338]], * Val accuracy / confusion: 67.88% / [[108, 122], [45, 245]] ------------------------------ Epoch 017 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.608908 - Iter 024 / 025, Loss: 0.414995 * Train accuracy / confusion: 67.00% / [[218, 137], [127, 318]], * Val accuracy / confusion: 71.54% / [[163, 67], [81, 209]] ------------------------------ Epoch 018 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.560425 - Iter 024 / 025, Loss: 0.655430 * Train accuracy / confusion: 68.88% / [[222, 135], [114, 329]], * Val accuracy / confusion: 74.62% / [[159, 71], [61, 229]] ------------------------------ Epoch 019 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.577732 - Iter 024 / 025, Loss: 0.622692 * Train accuracy / confusion: 69.62% / [[223, 130], [113, 334]], * Val accuracy / confusion: 68.46% / [[171, 59], [105, 185]] ------------------------------ Epoch 020 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.857862 - Iter 024 / 025, Loss: 0.555417 * Train accuracy / confusion: 68.62% / [[212, 146], [105, 337]], * Val accuracy / confusion: 73.08% / [[170, 60], [80, 210]] ------------------------------ Epoch 021 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547041 - Iter 024 / 025, Loss: 0.500190 * Train accuracy / confusion: 69.50% / [[220, 133], [111, 336]], * Val accuracy / confusion: 70.58% / [[186, 44], [109, 181]] ------------------------------ Epoch 022 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.807377 - Iter 024 / 025, Loss: 0.578335 * Train accuracy / confusion: 70.62% / [[219, 136], [99, 346]], * Val accuracy / confusion: 72.31% / [[137, 93], [51, 239]] ------------------------------ Epoch 023 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.599908 - Iter 024 / 025, Loss: 0.566754 * Train accuracy / confusion: 73.00% / [[232, 122], [94, 352]], * Val accuracy / confusion: 68.65% / [[95, 135], [28, 262]] ------------------------------ Epoch 024 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.496234 - Iter 024 / 025, Loss: 0.716418 * Train accuracy / confusion: 71.25% / [[229, 127], [103, 341]], * Val accuracy / confusion: 74.81% / [[142, 88], [43, 247]] ------------------------------ Epoch 025 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519655 - Iter 024 / 025, Loss: 0.476092 * Train accuracy / confusion: 70.62% / [[228, 132], [103, 337]], * Val accuracy / confusion: 66.35% / [[193, 37], [138, 152]] ------------------------------ Epoch 026 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547074 - Iter 024 / 025, Loss: 0.702853 * Train accuracy / confusion: 71.62% / [[233, 125], [102, 340]], * Val accuracy / confusion: 71.15% / [[181, 49], [101, 189]] ------------------------------ Epoch 027 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.571889 - Iter 024 / 025, Loss: 0.498432 * Train accuracy / confusion: 71.38% / [[235, 125], [104, 336]], * Val accuracy / confusion: 68.65% / [[169, 61], [102, 188]] ------------------------------ Epoch 028 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.585791 - Iter 024 / 025, Loss: 0.453591 * Train accuracy / confusion: 70.00% / [[242, 118], [122, 318]], * Val accuracy / confusion: 71.54% / [[124, 106], [42, 248]] ------------------------------ Epoch 029 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.606405 - Iter 024 / 025, Loss: 0.528360 * Train accuracy / confusion: 71.12% / [[232, 127], [104, 337]], * Val accuracy / confusion: 70.38% / [[197, 33], [121, 169]] ------------------------------ Epoch 030 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.639261 - Iter 024 / 025, Loss: 0.317520 * Train accuracy / confusion: 70.25% / [[220, 136], [102, 342]], * Val accuracy / confusion: 72.50% / [[152, 78], [65, 225]] ------------------------------ Epoch 031 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.533342 - Iter 024 / 025, Loss: 0.795424 * Train accuracy / confusion: 71.50% / [[240, 120], [108, 332]], * Val accuracy / confusion: 74.04% / [[131, 99], [36, 254]] ------------------------------ Epoch 032 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.502388 - Iter 024 / 025, Loss: 0.630581 * Train accuracy / confusion: 71.75% / [[230, 128], [98, 344]], * Val accuracy / confusion: 70.77% / [[107, 123], [29, 261]] ------------------------------ Epoch 033 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.580997 - Iter 024 / 025, Loss: 0.712912 * Train accuracy / confusion: 70.38% / [[220, 141], [96, 343]], * Val accuracy / confusion: 72.31% / [[170, 60], [84, 206]] ------------------------------ Epoch 034 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.768044 - Iter 024 / 025, Loss: 0.631189 * Train accuracy / confusion: 69.88% / [[229, 126], [115, 330]], * Val accuracy / confusion: 74.23% / [[156, 74], [60, 230]] ------------------------------ Epoch 035 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519004 - Iter 024 / 025, Loss: 0.532840 * Train accuracy / confusion: 70.88% / [[237, 117], [116, 330]], * Val accuracy / confusion: 69.81% / [[116, 114], [43, 247]] ------------------------------ Epoch 036 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591971 - Iter 024 / 025, Loss: 0.502953 * Train accuracy / confusion: 72.00% / [[224, 131], [93, 352]], * Val accuracy / confusion: 73.85% / [[148, 82], [54, 236]] ------------------------------ Epoch 037 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.532590 - Iter 024 / 025, Loss: 0.413745 * Train accuracy / confusion: 71.75% / [[241, 116], [110, 333]], * Val accuracy / confusion: 66.73% / [[82, 148], [25, 265]] ------------------------------ Epoch 038 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.608730 - Iter 024 / 025, Loss: 0.622856 * Train accuracy / confusion: 73.38% / [[242, 112], [101, 345]], * Val accuracy / confusion: 73.27% / [[135, 95], [44, 246]] ------------------------------ Epoch 039 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.492793 - Iter 024 / 025, Loss: 0.517565 * Train accuracy / confusion: 73.62% / [[239, 118], [93, 350]], * Val accuracy / confusion: 70.38% / [[185, 45], [109, 181]] ------------------------------ Epoch 040 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.536455 - Iter 024 / 025, Loss: 0.679880 * Train accuracy / confusion: 70.62% / [[246, 110], [125, 319]], * Val accuracy / confusion: 72.12% / [[166, 64], [81, 209]] ------------------------------ Epoch 041 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.347484 - Iter 024 / 025, Loss: 0.647148 * Train accuracy / confusion: 72.25% / [[230, 124], [98, 348]], * Val accuracy / confusion: 69.81% / [[170, 60], [97, 193]] ------------------------------ Epoch 042 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.635656 - Iter 024 / 025, Loss: 0.594038 * Train accuracy / confusion: 70.75% / [[223, 132], [102, 343]], * Val accuracy / confusion: 70.96% / [[172, 58], [93, 197]] ------------------------------ Epoch 043 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.560517 - Iter 024 / 025, Loss: 0.605391 * Train accuracy / confusion: 72.62% / [[251, 105], [114, 330]], * Val accuracy / confusion: 65.96% / [[75, 155], [22, 268]] ------------------------------ Epoch 044 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.513385 - Iter 024 / 025, Loss: 0.484819 * Train accuracy / confusion: 73.25% / [[237, 121], [93, 349]], * Val accuracy / confusion: 74.81% / [[148, 82], [49, 241]] ------------------------------ Epoch 045 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.557240 - Iter 024 / 025, Loss: 0.521607 * Train accuracy / confusion: 72.25% / [[237, 124], [98, 341]], * Val accuracy / confusion: 71.15% / [[186, 44], [106, 184]] ------------------------------ Epoch 046 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.530367 - Iter 024 / 025, Loss: 0.671148 * Train accuracy / confusion: 71.88% / [[230, 129], [96, 345]], * Val accuracy / confusion: 67.31% / [[76, 154], [16, 274]] ------------------------------ Epoch 047 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.645381 - Iter 024 / 025, Loss: 0.501910 * Train accuracy / confusion: 70.25% / [[226, 129], [109, 336]], * Val accuracy / confusion: 70.77% / [[108, 122], [30, 260]] ------------------------------ Epoch 048 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.399075 - Iter 024 / 025, Loss: 0.608781 * Train accuracy / confusion: 73.00% / [[236, 119], [97, 348]], * Val accuracy / confusion: 72.50% / [[139, 91], [52, 238]] ------------------------------ Epoch 049 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.609294 - Iter 024 / 025, Loss: 0.679103 * Train accuracy / confusion: 75.50% / [[243, 113], [83, 361]], * Val accuracy / confusion: 69.62% / [[111, 119], [39, 251]] ------------------------------ Epoch 050 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.501301 - Iter 024 / 025, Loss: 0.713621 * Train accuracy / confusion: 72.62% / [[238, 116], [103, 343]], * Val accuracy / confusion: 72.12% / [[174, 56], [89, 201]] ------------------------------ Epoch 051 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.541198 - Iter 024 / 025, Loss: 0.422830 * Train accuracy / confusion: 73.75% / [[239, 121], [89, 351]], * Val accuracy / confusion: 76.35% / [[161, 69], [54, 236]] ------------------------------ Epoch 052 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.536000 - Iter 024 / 025, Loss: 0.464390 * Train accuracy / confusion: 73.50% / [[242, 118], [94, 346]], * Val accuracy / confusion: 70.38% / [[102, 128], [26, 264]] ------------------------------ Epoch 053 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.377862 - Iter 024 / 025, Loss: 0.622659 * Train accuracy / confusion: 73.00% / [[234, 121], [95, 350]], * Val accuracy / confusion: 70.38% / [[180, 50], [104, 186]] ------------------------------ Epoch 054 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.657157 - Iter 024 / 025, Loss: 0.479540 * Train accuracy / confusion: 72.12% / [[233, 121], [102, 344]], * Val accuracy / confusion: 74.04% / [[136, 94], [41, 249]] ------------------------------ Epoch 055 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.487658 - Iter 024 / 025, Loss: 0.506298 * Train accuracy / confusion: 72.00% / [[234, 125], [99, 342]], * Val accuracy / confusion: 70.58% / [[163, 67], [86, 204]] ------------------------------ Epoch 056 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.452177 - Iter 024 / 025, Loss: 0.766109 * Train accuracy / confusion: 72.50% / [[239, 117], [103, 341]], * Val accuracy / confusion: 73.08% / [[161, 69], [71, 219]] ------------------------------ Epoch 057 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.480993 - Iter 024 / 025, Loss: 0.667073 * Train accuracy / confusion: 73.12% / [[239, 119], [96, 346]], * Val accuracy / confusion: 67.69% / [[82, 148], [20, 270]] ------------------------------ Epoch 058 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.672122 - Iter 024 / 025, Loss: 0.594653 * Train accuracy / confusion: 72.12% / [[238, 122], [101, 339]], * Val accuracy / confusion: 70.96% / [[166, 64], [87, 203]] ------------------------------ Epoch 059 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.516668 - Iter 024 / 025, Loss: 0.441185 * Train accuracy / confusion: 73.00% / [[239, 121], [95, 345]], * Val accuracy / confusion: 72.50% / [[162, 68], [75, 215]] ------------------------------ Epoch 060 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.438366 - Iter 024 / 025, Loss: 0.422833 * Train accuracy / confusion: 72.75% / [[238, 118], [100, 344]], * Val accuracy / confusion: 66.15% / [[184, 46], [130, 160]] ------------------------------ Epoch 061 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.570422 - Iter 024 / 025, Loss: 0.462901 * Train accuracy / confusion: 72.62% / [[248, 112], [107, 333]], * Val accuracy / confusion: 74.23% / [[144, 86], [48, 242]] ------------------------------ Epoch 062 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483543 - Iter 024 / 025, Loss: 0.391513 * Train accuracy / confusion: 73.38% / [[232, 124], [89, 355]], * Val accuracy / confusion: 68.27% / [[97, 133], [32, 258]] ------------------------------ Epoch 063 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.509258 - Iter 024 / 025, Loss: 0.580470 * Train accuracy / confusion: 74.88% / [[248, 110], [91, 351]], * Val accuracy / confusion: 71.73% / [[179, 51], [96, 194]] ------------------------------ Epoch 064 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.618768 - Iter 024 / 025, Loss: 0.532339 * Train accuracy / confusion: 70.75% / [[215, 142], [92, 351]], * Val accuracy / confusion: 69.81% / [[170, 60], [97, 193]] ------------------------------ Epoch 065 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.443293 - Iter 024 / 025, Loss: 0.504844 * Train accuracy / confusion: 72.38% / [[243, 115], [106, 336]], * Val accuracy / confusion: 75.96% / [[152, 78], [47, 243]] ------------------------------ Epoch 066 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.705820 - Iter 024 / 025, Loss: 0.520699 * Train accuracy / confusion: 74.62% / [[260, 99], [104, 337]], * Val accuracy / confusion: 72.88% / [[141, 89], [52, 238]] ------------------------------ Epoch 067 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.559605 - Iter 024 / 025, Loss: 0.584090 * Train accuracy / confusion: 74.00% / [[229, 130], [78, 363]], * Val accuracy / confusion: 74.81% / [[140, 90], [41, 249]] ------------------------------ Epoch 068 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473307 - Iter 024 / 025, Loss: 0.533713 * Train accuracy / confusion: 71.75% / [[225, 127], [99, 349]], * Val accuracy / confusion: 64.23% / [[62, 168], [18, 272]] ------------------------------ Epoch 069 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.339214 - Iter 024 / 025, Loss: 0.547664 * Train accuracy / confusion: 73.75% / [[241, 113], [97, 349]], * Val accuracy / confusion: 72.69% / [[179, 51], [91, 199]] ------------------------------ Epoch 070 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.555639 - Iter 024 / 025, Loss: 0.476916 * Train accuracy / confusion: 73.25% / [[236, 122], [92, 350]], * Val accuracy / confusion: 70.58% / [[152, 78], [75, 215]] ------------------------------ Epoch 071 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.610972 - Iter 024 / 025, Loss: 0.582394 * Train accuracy / confusion: 72.12% / [[230, 126], [97, 347]], * Val accuracy / confusion: 70.77% / [[189, 41], [111, 179]] ------------------------------ Epoch 072 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.542670 - Iter 024 / 025, Loss: 0.575532 * Train accuracy / confusion: 73.38% / [[241, 113], [100, 346]], * Val accuracy / confusion: 69.23% / [[107, 123], [37, 253]] ------------------------------ Epoch 073 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.695869 - Iter 024 / 025, Loss: 0.443732 * Train accuracy / confusion: 73.38% / [[237, 120], [93, 350]], * Val accuracy / confusion: 73.65% / [[142, 88], [49, 241]] ------------------------------ Epoch 074 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.422444 - Iter 024 / 025, Loss: 0.514922 * Train accuracy / confusion: 72.50% / [[233, 123], [97, 347]], * Val accuracy / confusion: 72.88% / [[121, 109], [32, 258]] ------------------------------ Epoch 075 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.511884 - Iter 024 / 025, Loss: 0.756984 * Train accuracy / confusion: 72.00% / [[226, 127], [97, 350]], * Val accuracy / confusion: 73.65% / [[184, 46], [91, 199]] ------------------------------ Epoch 076 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.460856 - Iter 024 / 025, Loss: 0.714721 * Train accuracy / confusion: 74.12% / [[242, 115], [92, 351]], * Val accuracy / confusion: 74.42% / [[144, 86], [47, 243]] ------------------------------ Epoch 077 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.530612 - Iter 024 / 025, Loss: 0.586131 * Train accuracy / confusion: 73.88% / [[253, 102], [107, 338]], * Val accuracy / confusion: 76.54% / [[144, 86], [36, 254]] ------------------------------ Epoch 078 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.418961 - Iter 024 / 025, Loss: 0.956404 * Train accuracy / confusion: 74.50% / [[240, 114], [90, 356]], * Val accuracy / confusion: 73.85% / [[153, 77], [59, 231]] ------------------------------ Epoch 079 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.446608 - Iter 024 / 025, Loss: 0.457246 * Train accuracy / confusion: 71.88% / [[227, 130], [95, 348]], * Val accuracy / confusion: 74.62% / [[141, 89], [43, 247]] ------------------------------ Epoch 080 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.361897 - Iter 024 / 025, Loss: 0.414961 * Train accuracy / confusion: 74.88% / [[251, 106], [95, 348]], * Val accuracy / confusion: 73.46% / [[116, 114], [24, 266]] ------------------------------ Epoch 081 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.543402 - Iter 024 / 025, Loss: 0.483937 * Train accuracy / confusion: 75.50% / [[257, 98], [98, 347]], * Val accuracy / confusion: 70.77% / [[187, 43], [109, 181]] ------------------------------ Epoch 082 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.507837 - Iter 024 / 025, Loss: 0.567645 * Train accuracy / confusion: 74.62% / [[235, 119], [84, 362]], * Val accuracy / confusion: 71.35% / [[111, 119], [30, 260]] ------------------------------ Epoch 083 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.485943 - Iter 024 / 025, Loss: 0.463420 * Train accuracy / confusion: 74.00% / [[257, 101], [107, 335]], * Val accuracy / confusion: 73.08% / [[167, 63], [77, 213]] ------------------------------ Epoch 084 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.622039 - Iter 024 / 025, Loss: 0.540579 * Train accuracy / confusion: 73.25% / [[231, 127], [87, 355]], * Val accuracy / confusion: 76.73% / [[160, 70], [51, 239]] ------------------------------ Epoch 085 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.688125 - Iter 024 / 025, Loss: 0.427872 * Train accuracy / confusion: 74.12% / [[246, 109], [98, 347]], * Val accuracy / confusion: 74.23% / [[152, 78], [56, 234]] ------------------------------ Epoch 086 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.633103 - Iter 024 / 025, Loss: 0.569817 * Train accuracy / confusion: 73.38% / [[236, 119], [94, 351]], * Val accuracy / confusion: 74.23% / [[147, 83], [51, 239]] ------------------------------ Epoch 087 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.497921 - Iter 024 / 025, Loss: 0.431101 * Train accuracy / confusion: 75.00% / [[249, 111], [89, 351]], * Val accuracy / confusion: 70.00% / [[129, 101], [55, 235]] ------------------------------ Epoch 088 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.518860 - Iter 024 / 025, Loss: 0.497715 * Train accuracy / confusion: 73.88% / [[234, 120], [89, 357]], * Val accuracy / confusion: 70.77% / [[172, 58], [94, 196]] ------------------------------ Epoch 089 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.472993 - Iter 024 / 025, Loss: 0.575407 * Train accuracy / confusion: 74.12% / [[235, 119], [88, 358]], * Val accuracy / confusion: 66.54% / [[71, 159], [15, 275]] ------------------------------ Epoch 090 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477026 - Iter 024 / 025, Loss: 0.561004 * Train accuracy / confusion: 73.75% / [[240, 116], [94, 350]], * Val accuracy / confusion: 72.12% / [[183, 47], [98, 192]] ------------------------------ Epoch 091 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.527011 - Iter 024 / 025, Loss: 0.554683 * Train accuracy / confusion: 75.50% / [[241, 111], [85, 363]], * Val accuracy / confusion: 73.08% / [[136, 94], [46, 244]] ------------------------------ Epoch 092 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488925 - Iter 024 / 025, Loss: 0.554835 * Train accuracy / confusion: 75.00% / [[243, 112], [88, 357]], * Val accuracy / confusion: 71.92% / [[120, 110], [36, 254]] ------------------------------ Epoch 093 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.504388 - Iter 024 / 025, Loss: 0.473752 * Train accuracy / confusion: 74.62% / [[241, 113], [90, 356]], * Val accuracy / confusion: 75.19% / [[143, 87], [42, 248]] ------------------------------ Epoch 094 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.453443 - Iter 024 / 025, Loss: 0.599131 * Train accuracy / confusion: 74.50% / [[239, 121], [83, 357]], * Val accuracy / confusion: 71.92% / [[177, 53], [93, 197]] ------------------------------ Epoch 095 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.709627 - Iter 024 / 025, Loss: 0.574356 * Train accuracy / confusion: 74.88% / [[251, 111], [90, 348]], * Val accuracy / confusion: 74.42% / [[132, 98], [35, 255]] ------------------------------ Epoch 096 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.640131 - Iter 024 / 025, Loss: 0.432010 * Train accuracy / confusion: 75.62% / [[247, 114], [81, 358]], * Val accuracy / confusion: 74.62% / [[130, 100], [32, 258]] ------------------------------ Epoch 097 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.545677 - Iter 024 / 025, Loss: 0.550575 * Train accuracy / confusion: 72.38% / [[238, 122], [99, 341]], * Val accuracy / confusion: 74.81% / [[180, 50], [81, 209]] ------------------------------ Epoch 098 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.459454 - Iter 024 / 025, Loss: 0.418692 * Train accuracy / confusion: 74.00% / [[254, 101], [107, 338]], * Val accuracy / confusion: 73.46% / [[149, 81], [57, 233]] ------------------------------ Epoch 099 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.514450 - Iter 024 / 025, Loss: 0.561559 * Train accuracy / confusion: 73.88% / [[229, 126], [83, 362]], * Val accuracy / confusion: 74.42% / [[168, 62], [71, 219]] ------------------------------ Epoch 100 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.630967 - Iter 024 / 025, Loss: 0.408642 * Train accuracy / confusion: 73.12% / [[251, 107], [108, 334]], * Val accuracy / confusion: 73.08% / [[135, 95], [45, 245]] ------------------------------ Epoch 101 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.503194 - Iter 024 / 025, Loss: 0.548594 * Train accuracy / confusion: 76.00% / [[242, 111], [81, 366]], * Val accuracy / confusion: 75.38% / [[168, 62], [66, 224]] ------------------------------ Epoch 102 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.493969 - Iter 024 / 025, Loss: 0.762572 * Train accuracy / confusion: 73.62% / [[251, 109], [102, 338]], * Val accuracy / confusion: 73.65% / [[140, 90], [47, 243]] ------------------------------ Epoch 103 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517041 - Iter 024 / 025, Loss: 0.801705 * Train accuracy / confusion: 74.75% / [[250, 107], [95, 348]], * Val accuracy / confusion: 71.54% / [[186, 44], [104, 186]] ------------------------------ Epoch 104 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.551155 - Iter 024 / 025, Loss: 0.436953 * Train accuracy / confusion: 74.88% / [[238, 115], [86, 361]], * Val accuracy / confusion: 74.04% / [[134, 96], [39, 251]] ------------------------------ Epoch 105 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.597770 - Iter 024 / 025, Loss: 0.449783 * Train accuracy / confusion: 75.75% / [[247, 108], [86, 359]], * Val accuracy / confusion: 73.85% / [[174, 56], [80, 210]] ------------------------------ Epoch 106 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.431018 - Iter 024 / 025, Loss: 0.416235 * Train accuracy / confusion: 73.62% / [[253, 105], [106, 336]], * Val accuracy / confusion: 65.96% / [[75, 155], [22, 268]] ------------------------------ Epoch 107 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.498629 - Iter 024 / 025, Loss: 0.711325 * Train accuracy / confusion: 73.62% / [[229, 129], [82, 360]], * Val accuracy / confusion: 70.77% / [[156, 74], [78, 212]] ------------------------------ Epoch 108 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.470790 - Iter 024 / 025, Loss: 0.481712 * Train accuracy / confusion: 74.25% / [[240, 120], [86, 354]], * Val accuracy / confusion: 74.62% / [[154, 76], [56, 234]] ------------------------------ Epoch 109 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.525944 - Iter 024 / 025, Loss: 0.537915 * Train accuracy / confusion: 75.62% / [[256, 101], [94, 349]], * Val accuracy / confusion: 75.00% / [[153, 77], [53, 237]] ------------------------------ Epoch 110 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.570424 - Iter 024 / 025, Loss: 0.424078 * Train accuracy / confusion: 74.38% / [[235, 121], [84, 360]], * Val accuracy / confusion: 70.58% / [[122, 108], [45, 245]] ------------------------------ Epoch 111 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.530709 - Iter 024 / 025, Loss: 0.436859 * Train accuracy / confusion: 75.12% / [[254, 106], [93, 347]], * Val accuracy / confusion: 73.27% / [[167, 63], [76, 214]] ------------------------------ Epoch 112 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.471329 - Iter 024 / 025, Loss: 0.469943 * Train accuracy / confusion: 74.25% / [[245, 115], [91, 349]], * Val accuracy / confusion: 74.04% / [[149, 81], [54, 236]] ------------------------------ Epoch 113 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.584402 - Iter 024 / 025, Loss: 0.667420 * Train accuracy / confusion: 74.25% / [[247, 105], [101, 347]], * Val accuracy / confusion: 71.35% / [[162, 68], [81, 209]] ------------------------------ Epoch 114 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466871 - Iter 024 / 025, Loss: 0.440729 * Train accuracy / confusion: 74.38% / [[233, 120], [85, 362]], * Val accuracy / confusion: 71.92% / [[121, 109], [37, 253]] ------------------------------ Epoch 115 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.405031 - Iter 024 / 025, Loss: 0.796355 * Train accuracy / confusion: 76.75% / [[263, 94], [92, 351]], * Val accuracy / confusion: 71.15% / [[177, 53], [97, 193]] ------------------------------ Epoch 116 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.475235 - Iter 024 / 025, Loss: 0.565602 * Train accuracy / confusion: 73.50% / [[246, 108], [104, 342]], * Val accuracy / confusion: 72.69% / [[137, 93], [49, 241]] ------------------------------ Epoch 117 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.590870 - Iter 024 / 025, Loss: 0.597569 * Train accuracy / confusion: 74.38% / [[245, 112], [93, 350]], * Val accuracy / confusion: 75.00% / [[138, 92], [38, 252]] ------------------------------ Epoch 118 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.447464 - Iter 024 / 025, Loss: 0.466181 * Train accuracy / confusion: 75.88% / [[254, 103], [90, 353]], * Val accuracy / confusion: 71.15% / [[116, 114], [36, 254]] ------------------------------ Epoch 119 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.544736 - Iter 024 / 025, Loss: 0.528189 * Train accuracy / confusion: 75.00% / [[240, 119], [81, 360]], * Val accuracy / confusion: 75.38% / [[170, 60], [68, 222]] ------------------------------ Epoch 120 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.475256 - Iter 024 / 025, Loss: 0.457641 * Train accuracy / confusion: 74.12% / [[254, 104], [103, 339]], * Val accuracy / confusion: 75.00% / [[158, 72], [58, 232]] ------------------------------ Epoch 121 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.447854 - Iter 024 / 025, Loss: 0.560019 * Train accuracy / confusion: 74.25% / [[226, 127], [79, 368]], * Val accuracy / confusion: 69.62% / [[100, 130], [28, 262]] ------------------------------ Epoch 122 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.533729 - Iter 024 / 025, Loss: 0.592912 * Train accuracy / confusion: 75.25% / [[255, 99], [99, 347]], * Val accuracy / confusion: 75.38% / [[159, 71], [57, 233]] ------------------------------ Epoch 123 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.442023 - Iter 024 / 025, Loss: 0.396433 * Train accuracy / confusion: 74.25% / [[227, 130], [76, 367]], * Val accuracy / confusion: 75.38% / [[164, 66], [62, 228]] ------------------------------ Epoch 124 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477642 - Iter 024 / 025, Loss: 0.621945 * Train accuracy / confusion: 75.88% / [[246, 109], [84, 361]], * Val accuracy / confusion: 73.65% / [[131, 99], [38, 252]] ------------------------------ Epoch 125 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591777 - Iter 024 / 025, Loss: 0.461339 * Train accuracy / confusion: 75.00% / [[250, 109], [91, 350]], * Val accuracy / confusion: 67.50% / [[84, 146], [23, 267]] ------------------------------ Epoch 126 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.560882 - Iter 024 / 025, Loss: 0.507497 * Train accuracy / confusion: 75.88% / [[251, 100], [93, 356]], * Val accuracy / confusion: 71.73% / [[142, 88], [59, 231]] ------------------------------ Epoch 127 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.561852 - Iter 024 / 025, Loss: 0.431781 * Train accuracy / confusion: 72.88% / [[241, 119], [98, 342]], * Val accuracy / confusion: 73.27% / [[159, 71], [68, 222]] ------------------------------ Epoch 128 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.552400 - Iter 024 / 025, Loss: 0.510149 * Train accuracy / confusion: 76.00% / [[242, 111], [81, 366]], * Val accuracy / confusion: 75.38% / [[161, 69], [59, 231]] ------------------------------ Epoch 129 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.500334 - Iter 024 / 025, Loss: 0.465066 * Train accuracy / confusion: 73.75% / [[247, 112], [98, 343]], * Val accuracy / confusion: 70.77% / [[111, 119], [33, 257]] ------------------------------ Epoch 130 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.586951 - Iter 024 / 025, Loss: 0.510405 * Train accuracy / confusion: 74.12% / [[240, 118], [89, 353]], * Val accuracy / confusion: 72.69% / [[132, 98], [44, 246]] ------------------------------ Epoch 131 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.525159 - Iter 024 / 025, Loss: 0.537797 * Train accuracy / confusion: 74.00% / [[242, 119], [89, 350]], * Val accuracy / confusion: 71.15% / [[134, 96], [54, 236]] ------------------------------ Epoch 132 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.489815 - Iter 024 / 025, Loss: 0.442831 * Train accuracy / confusion: 74.38% / [[241, 114], [91, 354]], * Val accuracy / confusion: 72.31% / [[145, 85], [59, 231]] ------------------------------ Epoch 133 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.713304 - Iter 024 / 025, Loss: 0.524336 * Train accuracy / confusion: 75.00% / [[243, 106], [94, 357]], * Val accuracy / confusion: 72.88% / [[150, 80], [61, 229]] ------------------------------ Epoch 134 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483621 - Iter 024 / 025, Loss: 0.361652 * Train accuracy / confusion: 76.88% / [[255, 98], [87, 360]], * Val accuracy / confusion: 71.15% / [[131, 99], [51, 239]] ------------------------------ Epoch 135 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.494410 - Iter 024 / 025, Loss: 0.557664 * Train accuracy / confusion: 73.00% / [[243, 110], [106, 341]], * Val accuracy / confusion: 76.73% / [[153, 77], [44, 246]] ------------------------------ Epoch 136 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.470741 - Iter 024 / 025, Loss: 0.638011 * Train accuracy / confusion: 74.38% / [[230, 127], [78, 365]], * Val accuracy / confusion: 73.27% / [[169, 61], [78, 212]] ------------------------------ Epoch 137 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.442829 - Iter 024 / 025, Loss: 0.445074 * Train accuracy / confusion: 76.38% / [[253, 103], [86, 358]], * Val accuracy / confusion: 67.31% / [[83, 147], [23, 267]] ------------------------------ Epoch 138 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.444968 - Iter 024 / 025, Loss: 0.634463 * Train accuracy / confusion: 74.12% / [[247, 113], [94, 346]], * Val accuracy / confusion: 74.04% / [[183, 47], [88, 202]] ------------------------------ Epoch 139 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464688 - Iter 024 / 025, Loss: 0.497714 * Train accuracy / confusion: 75.38% / [[249, 107], [90, 354]], * Val accuracy / confusion: 71.73% / [[121, 109], [38, 252]] ------------------------------ Epoch 140 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.497839 - Iter 024 / 025, Loss: 0.571310 * Train accuracy / confusion: 77.00% / [[260, 96], [88, 356]], * Val accuracy / confusion: 69.62% / [[180, 50], [108, 182]] ------------------------------ Epoch 141 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.627887 - Iter 024 / 025, Loss: 0.453445 * Train accuracy / confusion: 73.50% / [[231, 123], [89, 357]], * Val accuracy / confusion: 72.12% / [[126, 104], [41, 249]] ------------------------------ Epoch 142 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.543442 - Iter 024 / 025, Loss: 0.551788 * Train accuracy / confusion: 74.62% / [[252, 110], [93, 345]], * Val accuracy / confusion: 72.50% / [[122, 108], [35, 255]] ------------------------------ Epoch 143 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.496852 - Iter 024 / 025, Loss: 0.644265 * Train accuracy / confusion: 76.38% / [[265, 90], [99, 346]], * Val accuracy / confusion: 74.04% / [[162, 68], [67, 223]] ------------------------------ Epoch 144 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390223 - Iter 024 / 025, Loss: 0.741955 * Train accuracy / confusion: 73.62% / [[209, 142], [69, 380]], * Val accuracy / confusion: 73.46% / [[148, 82], [56, 234]] ------------------------------ Epoch 145 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464112 - Iter 024 / 025, Loss: 0.426166 * Train accuracy / confusion: 75.50% / [[248, 108], [88, 356]], * Val accuracy / confusion: 70.38% / [[111, 119], [35, 255]] ------------------------------ Epoch 146 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.375666 - Iter 024 / 025, Loss: 0.469700 * Train accuracy / confusion: 75.38% / [[255, 101], [96, 348]], * Val accuracy / confusion: 73.46% / [[173, 57], [81, 209]] ------------------------------ Epoch 147 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.683558 - Iter 024 / 025, Loss: 0.657289 * Train accuracy / confusion: 76.12% / [[246, 109], [82, 363]], * Val accuracy / confusion: 73.08% / [[133, 97], [43, 247]] ------------------------------ Epoch 148 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.334159 - Iter 024 / 025, Loss: 0.555792 * Train accuracy / confusion: 77.00% / [[264, 90], [94, 352]], * Val accuracy / confusion: 74.42% / [[166, 64], [69, 221]] ------------------------------ Epoch 149 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.474058 - Iter 024 / 025, Loss: 0.333938 * Train accuracy / confusion: 75.38% / [[249, 109], [88, 354]], * Val accuracy / confusion: 69.62% / [[98, 132], [26, 264]] ------------------------------ Epoch 150 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.659226 - Iter 024 / 025, Loss: 0.483887 * Train accuracy / confusion: 73.88% / [[252, 105], [104, 339]], * Val accuracy / confusion: 74.62% / [[150, 80], [52, 238]] ------------------------------ Epoch 151 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.539189 - Iter 024 / 025, Loss: 0.779844 * Train accuracy / confusion: 74.75% / [[260, 96], [106, 338]], * Val accuracy / confusion: 73.46% / [[137, 93], [45, 245]] ------------------------------ Epoch 152 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464434 - Iter 024 / 025, Loss: 0.481687 * Train accuracy / confusion: 76.00% / [[239, 119], [73, 369]], * Val accuracy / confusion: 74.04% / [[143, 87], [48, 242]] ------------------------------ Epoch 153 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.609749 - Iter 024 / 025, Loss: 0.542989 * Train accuracy / confusion: 76.00% / [[263, 97], [95, 345]], * Val accuracy / confusion: 74.62% / [[146, 84], [48, 242]] ------------------------------ Epoch 154 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591625 - Iter 024 / 025, Loss: 0.577348 * Train accuracy / confusion: 75.00% / [[240, 116], [84, 360]], * Val accuracy / confusion: 73.08% / [[159, 71], [69, 221]] ------------------------------ Epoch 155 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.422419 - Iter 024 / 025, Loss: 0.561623 * Train accuracy / confusion: 76.50% / [[256, 101], [87, 356]], * Val accuracy / confusion: 73.65% / [[135, 95], [42, 248]] ------------------------------ Epoch 156 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.436834 - Iter 024 / 025, Loss: 0.453971 * Train accuracy / confusion: 77.62% / [[269, 89], [90, 352]], * Val accuracy / confusion: 70.00% / [[117, 113], [43, 247]] ------------------------------ Epoch 157 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.364035 - Iter 024 / 025, Loss: 0.449800 * Train accuracy / confusion: 74.00% / [[241, 120], [88, 351]], * Val accuracy / confusion: 73.08% / [[153, 77], [63, 227]] ------------------------------ Epoch 158 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.396132 - Iter 024 / 025, Loss: 0.562629 * Train accuracy / confusion: 73.25% / [[251, 105], [109, 335]], * Val accuracy / confusion: 67.31% / [[191, 39], [131, 159]] ------------------------------ Epoch 159 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591792 - Iter 024 / 025, Loss: 0.445161 * Train accuracy / confusion: 75.38% / [[246, 110], [87, 357]], * Val accuracy / confusion: 70.77% / [[112, 118], [34, 256]] ------------------------------ Epoch 160 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.385510 - Iter 024 / 025, Loss: 0.705180 * Train accuracy / confusion: 75.25% / [[245, 111], [87, 357]], * Val accuracy / confusion: 71.15% / [[125, 105], [45, 245]] ------------------------------ Epoch 161 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.606724 - Iter 024 / 025, Loss: 0.475484 * Train accuracy / confusion: 75.75% / [[253, 104], [90, 353]], * Val accuracy / confusion: 69.81% / [[108, 122], [35, 255]] ------------------------------ Epoch 162 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.458337 - Iter 024 / 025, Loss: 0.480791 * Train accuracy / confusion: 74.88% / [[256, 101], [100, 343]], * Val accuracy / confusion: 75.19% / [[164, 66], [63, 227]] ------------------------------ Epoch 163 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.534563 - Iter 024 / 025, Loss: 0.525280 * Train accuracy / confusion: 75.88% / [[252, 105], [88, 355]], * Val accuracy / confusion: 74.62% / [[146, 84], [48, 242]] ------------------------------ Epoch 164 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.786668 - Iter 024 / 025, Loss: 0.551651 * Train accuracy / confusion: 75.75% / [[253, 103], [91, 353]], * Val accuracy / confusion: 71.73% / [[154, 76], [71, 219]] ------------------------------ Epoch 165 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.622939 - Iter 024 / 025, Loss: 0.457696 * Train accuracy / confusion: 76.75% / [[263, 96], [90, 351]], * Val accuracy / confusion: 73.85% / [[139, 91], [45, 245]] ------------------------------ Epoch 166 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430975 - Iter 024 / 025, Loss: 0.519676 * Train accuracy / confusion: 76.00% / [[243, 113], [79, 365]], * Val accuracy / confusion: 73.85% / [[149, 81], [55, 235]] ------------------------------ Epoch 167 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.446358 - Iter 024 / 025, Loss: 0.572947 * Train accuracy / confusion: 75.75% / [[255, 102], [92, 351]], * Val accuracy / confusion: 74.23% / [[146, 84], [50, 240]] ------------------------------ Epoch 168 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.529707 - Iter 024 / 025, Loss: 0.762477 * Train accuracy / confusion: 75.00% / [[241, 116], [84, 359]], * Val accuracy / confusion: 70.38% / [[110, 120], [34, 256]] ------------------------------ Epoch 169 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.794455 - Iter 024 / 025, Loss: 0.541444 * Train accuracy / confusion: 74.00% / [[239, 115], [93, 353]], * Val accuracy / confusion: 73.65% / [[158, 72], [65, 225]] ------------------------------ Epoch 170 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.388820 - Iter 024 / 025, Loss: 0.484851 * Train accuracy / confusion: 75.00% / [[256, 100], [100, 344]], * Val accuracy / confusion: 72.69% / [[149, 81], [61, 229]] ------------------------------ Epoch 171 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466655 - Iter 024 / 025, Loss: 0.615052 * Train accuracy / confusion: 76.25% / [[255, 100], [90, 355]], * Val accuracy / confusion: 72.69% / [[135, 95], [47, 243]] ------------------------------ Epoch 172 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.532587 - Iter 024 / 025, Loss: 0.600598 * Train accuracy / confusion: 76.62% / [[257, 98], [89, 356]], * Val accuracy / confusion: 73.85% / [[157, 73], [63, 227]] ------------------------------ Epoch 173 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.644514 - Iter 024 / 025, Loss: 0.651735 * Train accuracy / confusion: 74.88% / [[244, 111], [90, 355]], * Val accuracy / confusion: 75.19% / [[151, 79], [50, 240]] ------------------------------ Epoch 174 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.446418 - Iter 024 / 025, Loss: 0.475817 * Train accuracy / confusion: 76.75% / [[252, 107], [79, 362]], * Val accuracy / confusion: 74.23% / [[164, 66], [68, 222]] ------------------------------ Epoch 175 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.456285 - Iter 024 / 025, Loss: 0.393575 * Train accuracy / confusion: 75.88% / [[256, 102], [91, 351]], * Val accuracy / confusion: 72.69% / [[154, 76], [66, 224]] ------------------------------ Epoch 176 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.489058 - Iter 024 / 025, Loss: 0.596738 * Train accuracy / confusion: 74.62% / [[249, 110], [93, 348]], * Val accuracy / confusion: 74.23% / [[136, 94], [40, 250]] ------------------------------ Epoch 177 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.440832 - Iter 024 / 025, Loss: 0.863432 * Train accuracy / confusion: 74.62% / [[239, 117], [86, 358]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] ------------------------------ Epoch 178 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.537752 - Iter 024 / 025, Loss: 0.440848 * Train accuracy / confusion: 75.88% / [[257, 101], [92, 350]], * Val accuracy / confusion: 73.85% / [[170, 60], [76, 214]] ------------------------------ Epoch 179 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.531066 - Iter 024 / 025, Loss: 0.470091 * Train accuracy / confusion: 76.25% / [[265, 94], [96, 345]], * Val accuracy / confusion: 73.27% / [[136, 94], [45, 245]] ------------------------------ Epoch 180 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.530475 - Iter 024 / 025, Loss: 0.487059 * Train accuracy / confusion: 76.88% / [[262, 97], [88, 353]], * Val accuracy / confusion: 72.31% / [[149, 81], [63, 227]] ------------------------------ Epoch 181 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.540968 - Iter 024 / 025, Loss: 0.485934 * Train accuracy / confusion: 73.38% / [[237, 117], [96, 350]], * Val accuracy / confusion: 75.00% / [[152, 78], [52, 238]] ------------------------------ Epoch 182 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.578964 - Iter 024 / 025, Loss: 0.442983 * Train accuracy / confusion: 75.75% / [[264, 89], [105, 342]], * Val accuracy / confusion: 73.85% / [[164, 66], [70, 220]] ------------------------------ Epoch 183 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.575336 - Iter 024 / 025, Loss: 0.420783 * Train accuracy / confusion: 76.38% / [[255, 98], [91, 356]], * Val accuracy / confusion: 72.88% / [[175, 55], [86, 204]] ------------------------------ Epoch 184 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.356145 - Iter 024 / 025, Loss: 0.567708 * Train accuracy / confusion: 76.75% / [[257, 95], [91, 357]], * Val accuracy / confusion: 70.77% / [[116, 114], [38, 252]] ------------------------------ Epoch 185 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.476124 - Iter 024 / 025, Loss: 0.500964 * Train accuracy / confusion: 75.00% / [[256, 100], [100, 344]], * Val accuracy / confusion: 74.62% / [[159, 71], [61, 229]] ------------------------------ Epoch 186 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.475867 - Iter 024 / 025, Loss: 0.546893 * Train accuracy / confusion: 76.88% / [[256, 98], [87, 359]], * Val accuracy / confusion: 75.77% / [[162, 68], [58, 232]] ------------------------------ Epoch 187 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488078 - Iter 024 / 025, Loss: 0.330399 * Train accuracy / confusion: 76.00% / [[253, 104], [88, 355]], * Val accuracy / confusion: 73.65% / [[140, 90], [47, 243]] ------------------------------ Epoch 188 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.454703 - Iter 024 / 025, Loss: 0.571638 * Train accuracy / confusion: 74.75% / [[245, 115], [87, 353]], * Val accuracy / confusion: 74.42% / [[153, 77], [56, 234]] ------------------------------ Epoch 189 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.500931 - Iter 024 / 025, Loss: 0.648423 * Train accuracy / confusion: 76.00% / [[260, 101], [91, 348]], * Val accuracy / confusion: 74.62% / [[145, 85], [47, 243]] ------------------------------ Epoch 190 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.449096 - Iter 024 / 025, Loss: 0.586683 * Train accuracy / confusion: 78.25% / [[267, 93], [81, 359]], * Val accuracy / confusion: 69.62% / [[110, 120], [38, 252]] ------------------------------ Epoch 191 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.494378 - Iter 024 / 025, Loss: 0.569491 * Train accuracy / confusion: 75.38% / [[247, 106], [91, 356]], * Val accuracy / confusion: 73.46% / [[152, 78], [60, 230]] ------------------------------ Epoch 192 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.514912 - Iter 024 / 025, Loss: 0.475438 * Train accuracy / confusion: 75.75% / [[241, 114], [80, 365]], * Val accuracy / confusion: 72.50% / [[149, 81], [62, 228]] ------------------------------ Epoch 193 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.607988 - Iter 024 / 025, Loss: 0.409995 * Train accuracy / confusion: 76.00% / [[238, 115], [77, 370]], * Val accuracy / confusion: 73.85% / [[131, 99], [37, 253]] ------------------------------ Epoch 194 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.487851 - Iter 024 / 025, Loss: 0.413849 * Train accuracy / confusion: 76.38% / [[252, 111], [78, 359]], * Val accuracy / confusion: 70.58% / [[160, 70], [83, 207]] ------------------------------ Epoch 195 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.490900 - Iter 024 / 025, Loss: 0.422233 * Train accuracy / confusion: 77.12% / [[253, 98], [85, 364]], * Val accuracy / confusion: 70.77% / [[126, 104], [48, 242]] ------------------------------ Epoch 196 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.353200 - Iter 024 / 025, Loss: 0.411007 * Train accuracy / confusion: 75.00% / [[245, 112], [88, 355]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 197 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.600158 - Iter 024 / 025, Loss: 0.442030 * Train accuracy / confusion: 78.00% / [[262, 94], [82, 362]], * Val accuracy / confusion: 73.46% / [[177, 53], [85, 205]] ------------------------------ Epoch 198 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.468212 - Iter 024 / 025, Loss: 0.508250 * Train accuracy / confusion: 76.12% / [[245, 109], [82, 364]], * Val accuracy / confusion: 70.38% / [[110, 120], [34, 256]] ------------------------------ Epoch 199 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.568556 - Iter 024 / 025, Loss: 0.465504 * Train accuracy / confusion: 74.00% / [[251, 104], [104, 341]], * Val accuracy / confusion: 73.08% / [[133, 97], [43, 247]] ------------------------------ Epoch 200 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.515929 - Iter 024 / 025, Loss: 0.542006 * Train accuracy / confusion: 77.12% / [[253, 100], [83, 364]], * Val accuracy / confusion: 74.42% / [[138, 92], [41, 249]] ------------------------------ Epoch 201 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.425160 - Iter 024 / 025, Loss: 0.420822 * Train accuracy / confusion: 76.88% / [[256, 103], [82, 359]], * Val accuracy / confusion: 72.50% / [[144, 86], [57, 233]] ------------------------------ Epoch 202 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342128 - Iter 024 / 025, Loss: 0.601861 * Train accuracy / confusion: 75.25% / [[247, 116], [82, 355]], * Val accuracy / confusion: 75.77% / [[151, 79], [47, 243]] ------------------------------ Epoch 203 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.405810 - Iter 024 / 025, Loss: 0.462224 * Train accuracy / confusion: 77.50% / [[256, 95], [85, 364]], * Val accuracy / confusion: 71.92% / [[136, 94], [52, 238]] ------------------------------ Epoch 204 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.611254 - Iter 024 / 025, Loss: 0.430404 * Train accuracy / confusion: 77.50% / [[256, 102], [78, 364]], * Val accuracy / confusion: 74.23% / [[144, 86], [48, 242]] ------------------------------ Epoch 205 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.333229 - Iter 024 / 025, Loss: 0.382966 * Train accuracy / confusion: 75.38% / [[251, 111], [86, 352]], * Val accuracy / confusion: 73.85% / [[138, 92], [44, 246]] ------------------------------ Epoch 206 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.429022 - Iter 024 / 025, Loss: 0.351609 * Train accuracy / confusion: 75.88% / [[254, 106], [87, 353]], * Val accuracy / confusion: 73.08% / [[141, 89], [51, 239]] ------------------------------ Epoch 207 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.439340 - Iter 024 / 025, Loss: 0.579127 * Train accuracy / confusion: 76.75% / [[257, 100], [86, 357]], * Val accuracy / confusion: 71.15% / [[141, 89], [61, 229]] ------------------------------ Epoch 208 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.462666 - Iter 024 / 025, Loss: 0.536646 * Train accuracy / confusion: 77.25% / [[263, 95], [87, 355]], * Val accuracy / confusion: 75.38% / [[149, 81], [47, 243]] ------------------------------ Epoch 209 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.493904 - Iter 024 / 025, Loss: 0.467040 * Train accuracy / confusion: 76.38% / [[254, 105], [84, 357]], * Val accuracy / confusion: 74.23% / [[150, 80], [54, 236]] ------------------------------ Epoch 210 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.608331 - Iter 024 / 025, Loss: 0.510435 * Train accuracy / confusion: 76.25% / [[259, 95], [95, 351]], * Val accuracy / confusion: 72.88% / [[140, 90], [51, 239]] ------------------------------ Epoch 211 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.431700 - Iter 024 / 025, Loss: 0.429632 * Train accuracy / confusion: 77.75% / [[262, 97], [81, 360]], * Val accuracy / confusion: 74.42% / [[144, 86], [47, 243]] ------------------------------ Epoch 212 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.336932 - Iter 024 / 025, Loss: 0.315562 * Train accuracy / confusion: 77.00% / [[247, 110], [74, 369]], * Val accuracy / confusion: 75.77% / [[154, 76], [50, 240]] ------------------------------ Epoch 213 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.400085 - Iter 024 / 025, Loss: 0.467005 * Train accuracy / confusion: 77.00% / [[255, 100], [84, 361]], * Val accuracy / confusion: 74.23% / [[145, 85], [49, 241]] ------------------------------ Epoch 214 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.480807 - Iter 024 / 025, Loss: 0.578700 * Train accuracy / confusion: 79.12% / [[268, 84], [83, 365]], * Val accuracy / confusion: 76.35% / [[156, 74], [49, 241]] ------------------------------ Epoch 215 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.407170 - Iter 024 / 025, Loss: 0.434231 * Train accuracy / confusion: 76.75% / [[255, 97], [89, 359]], * Val accuracy / confusion: 73.27% / [[147, 83], [56, 234]] ------------------------------ Epoch 216 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.607561 - Iter 024 / 025, Loss: 0.566138 * Train accuracy / confusion: 78.50% / [[259, 96], [76, 369]], * Val accuracy / confusion: 75.38% / [[151, 79], [49, 241]] ------------------------------ Epoch 217 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.500769 - Iter 024 / 025, Loss: 0.433632 * Train accuracy / confusion: 79.00% / [[253, 99], [69, 379]], * Val accuracy / confusion: 73.08% / [[147, 83], [57, 233]] ------------------------------ Epoch 218 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.476258 - Iter 024 / 025, Loss: 0.438109 * Train accuracy / confusion: 78.62% / [[261, 93], [78, 368]], * Val accuracy / confusion: 73.08% / [[144, 86], [54, 236]] ------------------------------ Epoch 219 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.612060 - Iter 024 / 025, Loss: 0.563838 * Train accuracy / confusion: 77.88% / [[263, 91], [86, 360]], * Val accuracy / confusion: 73.65% / [[150, 80], [57, 233]] ------------------------------ Epoch 220 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.487346 - Iter 024 / 025, Loss: 0.588326 * Train accuracy / confusion: 78.88% / [[265, 92], [77, 366]], * Val accuracy / confusion: 72.69% / [[136, 94], [48, 242]] ------------------------------ Epoch 221 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.282216 - Iter 024 / 025, Loss: 0.388707 * Train accuracy / confusion: 79.38% / [[268, 92], [73, 367]], * Val accuracy / confusion: 73.27% / [[142, 88], [51, 239]] ------------------------------ Epoch 222 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.448109 - Iter 024 / 025, Loss: 0.646944 * Train accuracy / confusion: 77.12% / [[255, 99], [84, 362]], * Val accuracy / confusion: 71.15% / [[147, 83], [67, 223]] ------------------------------ Epoch 223 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.508453 - Iter 024 / 025, Loss: 0.558281 * Train accuracy / confusion: 78.75% / [[263, 89], [81, 367]], * Val accuracy / confusion: 74.62% / [[154, 76], [56, 234]] ------------------------------ Epoch 224 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.391232 - Iter 024 / 025, Loss: 0.332201 * Train accuracy / confusion: 76.62% / [[253, 100], [87, 360]], * Val accuracy / confusion: 71.73% / [[135, 95], [52, 238]] ------------------------------ Epoch 225 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.457894 - Iter 024 / 025, Loss: 0.347979 * Train accuracy / confusion: 77.38% / [[256, 102], [79, 363]], * Val accuracy / confusion: 75.58% / [[155, 75], [52, 238]] ------------------------------ Epoch 226 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.582879 - Iter 024 / 025, Loss: 0.516595 * Train accuracy / confusion: 76.88% / [[258, 97], [88, 357]], * Val accuracy / confusion: 72.69% / [[140, 90], [52, 238]] ------------------------------ Epoch 227 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.463183 - Iter 024 / 025, Loss: 0.529915 * Train accuracy / confusion: 76.38% / [[255, 106], [83, 356]], * Val accuracy / confusion: 73.85% / [[146, 84], [52, 238]] ------------------------------ Epoch 228 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.577098 - Iter 024 / 025, Loss: 0.502616 * Train accuracy / confusion: 77.25% / [[255, 99], [83, 363]], * Val accuracy / confusion: 71.92% / [[142, 88], [58, 232]] ------------------------------ Epoch 229 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.381487 - Iter 024 / 025, Loss: 0.361464 * Train accuracy / confusion: 78.38% / [[263, 90], [83, 364]], * Val accuracy / confusion: 74.42% / [[153, 77], [56, 234]] ------------------------------ Epoch 230 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.396875 - Iter 024 / 025, Loss: 0.412755 * Train accuracy / confusion: 77.62% / [[255, 99], [80, 366]], * Val accuracy / confusion: 76.15% / [[152, 78], [46, 244]] ------------------------------ Epoch 231 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.419768 - Iter 024 / 025, Loss: 0.454898 * Train accuracy / confusion: 75.50% / [[248, 107], [89, 356]], * Val accuracy / confusion: 71.73% / [[137, 93], [54, 236]] ------------------------------ Epoch 232 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.440410 - Iter 024 / 025, Loss: 0.374157 * Train accuracy / confusion: 78.25% / [[265, 91], [83, 361]], * Val accuracy / confusion: 71.35% / [[142, 88], [61, 229]] ------------------------------ Epoch 233 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.585422 - Iter 024 / 025, Loss: 0.547330 * Train accuracy / confusion: 76.88% / [[252, 100], [85, 363]], * Val accuracy / confusion: 71.15% / [[146, 84], [66, 224]] ------------------------------ Epoch 234 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.493221 - Iter 024 / 025, Loss: 0.391535 * Train accuracy / confusion: 76.62% / [[253, 99], [88, 360]], * Val accuracy / confusion: 72.31% / [[141, 89], [55, 235]] ------------------------------ Epoch 235 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.501221 - Iter 024 / 025, Loss: 0.476330 * Train accuracy / confusion: 76.62% / [[253, 106], [81, 360]], * Val accuracy / confusion: 72.50% / [[139, 91], [52, 238]] ------------------------------ Epoch 236 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.415695 - Iter 024 / 025, Loss: 0.384893 * Train accuracy / confusion: 79.12% / [[260, 96], [71, 373]], * Val accuracy / confusion: 74.42% / [[150, 80], [53, 237]] ------------------------------ Epoch 237 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.520293 - Iter 024 / 025, Loss: 0.465846 * Train accuracy / confusion: 78.12% / [[258, 99], [76, 367]], * Val accuracy / confusion: 72.69% / [[140, 90], [52, 238]] ------------------------------ Epoch 238 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357949 - Iter 024 / 025, Loss: 0.334350 * Train accuracy / confusion: 79.38% / [[270, 87], [78, 365]], * Val accuracy / confusion: 73.46% / [[151, 79], [59, 231]] ------------------------------ Epoch 239 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.455659 - Iter 024 / 025, Loss: 0.350349 * Train accuracy / confusion: 79.25% / [[267, 88], [78, 367]], * Val accuracy / confusion: 70.00% / [[132, 98], [58, 232]] ------------------------------ Epoch 240 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.461476 - Iter 024 / 025, Loss: 0.522382 * Train accuracy / confusion: 75.25% / [[260, 102], [96, 342]], * Val accuracy / confusion: 71.92% / [[143, 87], [59, 231]] ------------------------------ Epoch 241 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.423308 - Iter 024 / 025, Loss: 0.396343 * Train accuracy / confusion: 75.62% / [[246, 115], [80, 359]], * Val accuracy / confusion: 72.88% / [[137, 93], [48, 242]] ------------------------------ Epoch 242 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.524533 - Iter 024 / 025, Loss: 0.483848 * Train accuracy / confusion: 78.88% / [[259, 98], [71, 372]], * Val accuracy / confusion: 73.85% / [[146, 84], [52, 238]] ------------------------------ Epoch 243 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.412207 - Iter 024 / 025, Loss: 0.456518 * Train accuracy / confusion: 79.12% / [[262, 89], [78, 371]], * Val accuracy / confusion: 70.77% / [[133, 97], [55, 235]] ------------------------------ Epoch 244 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.582359 - Iter 024 / 025, Loss: 0.387593 * Train accuracy / confusion: 77.12% / [[249, 106], [77, 368]], * Val accuracy / confusion: 71.73% / [[140, 90], [57, 233]] ------------------------------ Epoch 245 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.517502 - Iter 024 / 025, Loss: 0.414433 * Train accuracy / confusion: 80.25% / [[259, 93], [65, 383]], * Val accuracy / confusion: 70.96% / [[129, 101], [50, 240]] ------------------------------ Epoch 246 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.452324 - Iter 024 / 025, Loss: 0.456650 * Train accuracy / confusion: 76.50% / [[254, 103], [85, 358]], * Val accuracy / confusion: 72.69% / [[145, 85], [57, 233]] ------------------------------ Epoch 247 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.483286 - Iter 024 / 025, Loss: 0.520269 * Train accuracy / confusion: 78.62% / [[263, 91], [80, 366]], * Val accuracy / confusion: 70.96% / [[137, 93], [58, 232]] ------------------------------ Epoch 248 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.567319 - Iter 024 / 025, Loss: 0.437188 * Train accuracy / confusion: 77.38% / [[262, 97], [84, 357]], * Val accuracy / confusion: 73.46% / [[156, 74], [64, 226]] ------------------------------ Epoch 249 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.552439 - Iter 024 / 025, Loss: 0.480247 * Train accuracy / confusion: 77.50% / [[261, 98], [82, 359]], * Val accuracy / confusion: 73.65% / [[144, 86], [51, 239]] ------------------------------ Epoch 250 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.568731 - Iter 024 / 025, Loss: 0.528804 * Train accuracy / confusion: 77.62% / [[254, 98], [81, 367]], * Val accuracy / confusion: 72.88% / [[143, 87], [54, 236]] ------------------------------ Epoch 251 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.516275 - Iter 024 / 025, Loss: 0.462642 * Train accuracy / confusion: 78.00% / [[265, 94], [82, 359]], * Val accuracy / confusion: 74.23% / [[147, 83], [51, 239]] ------------------------------ Epoch 252 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.486426 - Iter 024 / 025, Loss: 0.472173 * Train accuracy / confusion: 79.00% / [[262, 93], [75, 370]], * Val accuracy / confusion: 73.27% / [[143, 87], [52, 238]] ------------------------------ Epoch 253 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.522204 - Iter 024 / 025, Loss: 0.526461 * Train accuracy / confusion: 77.62% / [[254, 101], [78, 367]], * Val accuracy / confusion: 73.46% / [[149, 81], [57, 233]] ------------------------------ Epoch 254 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.381488 - Iter 024 / 025, Loss: 0.451113 * Train accuracy / confusion: 78.38% / [[265, 95], [78, 362]], * Val accuracy / confusion: 70.58% / [[137, 93], [60, 230]] ------------------------------ Epoch 255 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.533212 - Iter 024 / 025, Loss: 0.463032 * Train accuracy / confusion: 78.25% / [[265, 94], [80, 361]], * Val accuracy / confusion: 71.35% / [[138, 92], [57, 233]] ------------------------------ Epoch 256 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.519600 - Iter 024 / 025, Loss: 0.528196 * Train accuracy / confusion: 79.00% / [[263, 92], [76, 369]], * Val accuracy / confusion: 71.92% / [[137, 93], [53, 237]] ------------------------------ Epoch 257 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.532796 - Iter 024 / 025, Loss: 0.459657 * Train accuracy / confusion: 78.00% / [[266, 88], [88, 358]], * Val accuracy / confusion: 71.92% / [[139, 91], [55, 235]] ------------------------------ Epoch 258 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.298147 - Iter 024 / 025, Loss: 0.400878 * Train accuracy / confusion: 78.00% / [[265, 92], [84, 359]], * Val accuracy / confusion: 72.69% / [[147, 83], [59, 231]] ------------------------------ Epoch 259 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.464279 - Iter 024 / 025, Loss: 0.499940 * Train accuracy / confusion: 78.12% / [[260, 101], [74, 365]], * Val accuracy / confusion: 74.23% / [[151, 79], [55, 235]] ------------------------------ Epoch 260 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.547994 - Iter 024 / 025, Loss: 0.423670 * Train accuracy / confusion: 76.62% / [[249, 106], [81, 364]], * Val accuracy / confusion: 72.31% / [[137, 93], [51, 239]] ------------------------------ Epoch 261 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.467229 - Iter 024 / 025, Loss: 0.681426 * Train accuracy / confusion: 78.25% / [[257, 97], [77, 369]], * Val accuracy / confusion: 72.12% / [[140, 90], [55, 235]] ------------------------------ Epoch 262 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.402468 - Iter 024 / 025, Loss: 0.363551 * Train accuracy / confusion: 77.88% / [[259, 99], [78, 364]], * Val accuracy / confusion: 73.27% / [[147, 83], [56, 234]] ------------------------------ Epoch 263 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.458657 - Iter 024 / 025, Loss: 0.541723 * Train accuracy / confusion: 78.38% / [[261, 93], [80, 366]], * Val accuracy / confusion: 73.27% / [[140, 90], [49, 241]] ------------------------------ Epoch 264 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.641837 - Iter 024 / 025, Loss: 0.460998 * Train accuracy / confusion: 77.75% / [[259, 98], [80, 363]], * Val accuracy / confusion: 73.85% / [[144, 86], [50, 240]] ------------------------------ Epoch 265 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.409825 - Iter 024 / 025, Loss: 0.386888 * Train accuracy / confusion: 78.00% / [[259, 99], [77, 365]], * Val accuracy / confusion: 72.69% / [[145, 85], [57, 233]] ------------------------------ Epoch 266 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.496969 - Iter 024 / 025, Loss: 0.463868 * Train accuracy / confusion: 79.00% / [[269, 92], [76, 363]], * Val accuracy / confusion: 74.42% / [[153, 77], [56, 234]] ------------------------------ Epoch 267 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.454605 - Iter 024 / 025, Loss: 0.547052 * Train accuracy / confusion: 78.62% / [[261, 96], [75, 368]], * Val accuracy / confusion: 70.00% / [[133, 97], [59, 231]] ------------------------------ Epoch 268 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.439072 - Iter 024 / 025, Loss: 0.460357 * Train accuracy / confusion: 78.25% / [[256, 101], [73, 370]], * Val accuracy / confusion: 73.85% / [[145, 85], [51, 239]] ------------------------------ Epoch 269 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.301173 - Iter 024 / 025, Loss: 0.481803 * Train accuracy / confusion: 77.12% / [[261, 100], [83, 356]], * Val accuracy / confusion: 72.50% / [[140, 90], [53, 237]] ------------------------------ Epoch 270 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.583545 - Iter 024 / 025, Loss: 0.440092 * Train accuracy / confusion: 77.62% / [[259, 91], [88, 362]], * Val accuracy / confusion: 73.85% / [[139, 91], [45, 245]] ------------------------------ Epoch 271 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.415551 - Iter 024 / 025, Loss: 0.375732 * Train accuracy / confusion: 78.38% / [[254, 102], [71, 373]], * Val accuracy / confusion: 73.65% / [[143, 87], [50, 240]] ------------------------------ Epoch 272 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.481338 - Iter 024 / 025, Loss: 0.475132 * Train accuracy / confusion: 77.38% / [[258, 100], [81, 361]], * Val accuracy / confusion: 74.04% / [[141, 89], [46, 244]] ------------------------------ Epoch 273 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.433193 - Iter 024 / 025, Loss: 0.437068 * Train accuracy / confusion: 79.12% / [[262, 90], [77, 371]], * Val accuracy / confusion: 71.15% / [[132, 98], [52, 238]] ------------------------------ Epoch 274 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.433441 - Iter 024 / 025, Loss: 0.413632 * Train accuracy / confusion: 80.12% / [[262, 93], [66, 379]], * Val accuracy / confusion: 74.62% / [[148, 82], [50, 240]] ------------------------------ Epoch 275 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.500514 - Iter 024 / 025, Loss: 0.441108 * Train accuracy / confusion: 77.75% / [[248, 108], [70, 374]], * Val accuracy / confusion: 74.42% / [[153, 77], [56, 234]] ------------------------------ Epoch 276 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.506233 - Iter 024 / 025, Loss: 0.332247 * Train accuracy / confusion: 78.50% / [[263, 95], [77, 365]], * Val accuracy / confusion: 72.88% / [[147, 83], [58, 232]] ------------------------------ Epoch 277 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.383909 - Iter 024 / 025, Loss: 0.338321 * Train accuracy / confusion: 78.00% / [[262, 94], [82, 362]], * Val accuracy / confusion: 72.31% / [[142, 88], [56, 234]] ------------------------------ Epoch 278 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.388999 - Iter 024 / 025, Loss: 0.399994 * Train accuracy / confusion: 77.00% / [[257, 99], [85, 359]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 279 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.714212 - Iter 024 / 025, Loss: 0.574008 * Train accuracy / confusion: 78.38% / [[258, 99], [74, 369]], * Val accuracy / confusion: 73.65% / [[152, 78], [59, 231]] ------------------------------ Epoch 280 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.410322 - Iter 024 / 025, Loss: 0.259695 * Train accuracy / confusion: 79.00% / [[267, 92], [76, 365]], * Val accuracy / confusion: 71.73% / [[140, 90], [57, 233]] ------------------------------ Epoch 281 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.461701 - Iter 024 / 025, Loss: 0.371614 * Train accuracy / confusion: 77.75% / [[256, 97], [81, 366]], * Val accuracy / confusion: 74.23% / [[145, 85], [49, 241]] ------------------------------ Epoch 282 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.433363 - Iter 024 / 025, Loss: 0.575306 * Train accuracy / confusion: 78.38% / [[263, 96], [77, 364]], * Val accuracy / confusion: 73.46% / [[143, 87], [51, 239]] ------------------------------ Epoch 283 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.632043 - Iter 024 / 025, Loss: 0.645183 * Train accuracy / confusion: 78.38% / [[256, 103], [70, 371]], * Val accuracy / confusion: 73.65% / [[149, 81], [56, 234]] ------------------------------ Epoch 284 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.648633 - Iter 024 / 025, Loss: 0.381989 * Train accuracy / confusion: 80.00% / [[265, 92], [68, 375]], * Val accuracy / confusion: 70.96% / [[147, 83], [68, 222]] ------------------------------ Epoch 285 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.314352 - Iter 024 / 025, Loss: 0.525606 * Train accuracy / confusion: 78.12% / [[261, 95], [80, 364]], * Val accuracy / confusion: 71.73% / [[135, 95], [52, 238]] ------------------------------ Epoch 286 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.283520 - Iter 024 / 025, Loss: 0.327507 * Train accuracy / confusion: 78.38% / [[262, 94], [79, 365]], * Val accuracy / confusion: 72.69% / [[147, 83], [59, 231]] ------------------------------ Epoch 287 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.365777 - Iter 024 / 025, Loss: 0.341704 * Train accuracy / confusion: 77.50% / [[257, 103], [77, 363]], * Val accuracy / confusion: 73.27% / [[151, 79], [60, 230]] ------------------------------ Epoch 288 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342251 - Iter 024 / 025, Loss: 0.398380 * Train accuracy / confusion: 79.50% / [[263, 89], [75, 373]], * Val accuracy / confusion: 73.65% / [[146, 84], [53, 237]] ------------------------------ Epoch 289 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.375691 - Iter 024 / 025, Loss: 0.627801 * Train accuracy / confusion: 77.75% / [[262, 97], [81, 360]], * Val accuracy / confusion: 72.31% / [[152, 78], [66, 224]] ------------------------------ Epoch 290 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.468674 - Iter 024 / 025, Loss: 0.412705 * Train accuracy / confusion: 76.62% / [[255, 100], [87, 358]], * Val accuracy / confusion: 72.31% / [[145, 85], [59, 231]] ------------------------------ Epoch 291 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.553078 - Iter 024 / 025, Loss: 0.554170 * Train accuracy / confusion: 77.50% / [[263, 99], [81, 357]], * Val accuracy / confusion: 71.54% / [[144, 86], [62, 228]] ------------------------------ Epoch 292 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.424086 - Iter 024 / 025, Loss: 0.540096 * Train accuracy / confusion: 77.00% / [[256, 103], [81, 360]], * Val accuracy / confusion: 74.62% / [[149, 81], [51, 239]] ------------------------------ Epoch 293 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.564201 - Iter 024 / 025, Loss: 0.442137 * Train accuracy / confusion: 78.25% / [[261, 94], [80, 365]], * Val accuracy / confusion: 72.31% / [[135, 95], [49, 241]] ------------------------------ Epoch 294 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.601766 - Iter 024 / 025, Loss: 0.469804 * Train accuracy / confusion: 77.62% / [[260, 98], [81, 361]], * Val accuracy / confusion: 71.73% / [[141, 89], [58, 232]] ------------------------------ Epoch 295 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.296482 - Iter 024 / 025, Loss: 0.378306 * Train accuracy / confusion: 78.25% / [[270, 86], [88, 356]], * Val accuracy / confusion: 72.12% / [[139, 91], [54, 236]] ------------------------------ Epoch 296 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.461709 - Iter 024 / 025, Loss: 0.388660 * Train accuracy / confusion: 77.62% / [[258, 97], [82, 363]], * Val accuracy / confusion: 70.19% / [[134, 96], [59, 231]] ------------------------------ Epoch 297 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.518608 - Iter 024 / 025, Loss: 0.429534 * Train accuracy / confusion: 77.50% / [[256, 102], [78, 364]], * Val accuracy / confusion: 73.08% / [[139, 91], [49, 241]] ------------------------------ Epoch 298 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342648 - Iter 024 / 025, Loss: 0.396637 * Train accuracy / confusion: 77.50% / [[261, 100], [80, 359]], * Val accuracy / confusion: 70.00% / [[122, 108], [48, 242]] ------------------------------ Epoch 299 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.542719 - Iter 024 / 025, Loss: 0.487357 * Train accuracy / confusion: 77.88% / [[259, 95], [82, 364]], * Val accuracy / confusion: 73.46% / [[149, 81], [57, 233]] ------------------------------ Epoch 300 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.329700 - Iter 024 / 025, Loss: 0.432929 * Train accuracy / confusion: 77.00% / [[261, 99], [85, 355]], * Val accuracy / confusion: 71.73% / [[132, 98], [49, 241]] ------------------------------ Epoch 301 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.633999 - Iter 024 / 025, Loss: 0.407445 * Train accuracy / confusion: 79.00% / [[269, 92], [76, 363]], * Val accuracy / confusion: 75.38% / [[147, 83], [45, 245]] ------------------------------ Epoch 302 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.387802 - Iter 024 / 025, Loss: 0.654314 * Train accuracy / confusion: 79.38% / [[269, 88], [77, 366]], * Val accuracy / confusion: 73.46% / [[144, 86], [52, 238]] ------------------------------ Epoch 303 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.378322 - Iter 024 / 025, Loss: 0.634686 * Train accuracy / confusion: 77.62% / [[252, 99], [80, 369]], * Val accuracy / confusion: 72.50% / [[146, 84], [59, 231]] ------------------------------ Epoch 304 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.406249 - Iter 024 / 025, Loss: 0.447888 * Train accuracy / confusion: 79.00% / [[265, 92], [76, 367]], * Val accuracy / confusion: 70.58% / [[134, 96], [57, 233]] ------------------------------ Epoch 305 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.373772 - Iter 024 / 025, Loss: 0.457842 * Train accuracy / confusion: 77.88% / [[263, 96], [81, 360]], * Val accuracy / confusion: 71.15% / [[146, 84], [66, 224]] ------------------------------ Epoch 306 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.490053 - Iter 024 / 025, Loss: 0.407370 * Train accuracy / confusion: 76.50% / [[261, 101], [87, 351]], * Val accuracy / confusion: 71.92% / [[147, 83], [63, 227]] ------------------------------ Epoch 307 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.468255 - Iter 024 / 025, Loss: 0.516722 * Train accuracy / confusion: 78.38% / [[264, 91], [82, 363]], * Val accuracy / confusion: 71.54% / [[136, 94], [54, 236]] ------------------------------ Epoch 308 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.458665 - Iter 024 / 025, Loss: 0.368646 * Train accuracy / confusion: 79.75% / [[264, 90], [72, 374]], * Val accuracy / confusion: 72.69% / [[136, 94], [48, 242]] ------------------------------ Epoch 309 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.601798 - Iter 024 / 025, Loss: 0.454254 * Train accuracy / confusion: 79.62% / [[263, 92], [71, 374]], * Val accuracy / confusion: 71.35% / [[140, 90], [59, 231]] ------------------------------ Epoch 310 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.304186 - Iter 024 / 025, Loss: 0.481232 * Train accuracy / confusion: 79.25% / [[269, 87], [79, 365]], * Val accuracy / confusion: 71.92% / [[139, 91], [55, 235]] ------------------------------ Epoch 311 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.789515 - Iter 024 / 025, Loss: 0.538731 * Train accuracy / confusion: 77.25% / [[259, 95], [87, 359]], * Val accuracy / confusion: 73.46% / [[140, 90], [48, 242]] ------------------------------ Epoch 312 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.436879 - Iter 024 / 025, Loss: 0.363006 * Train accuracy / confusion: 79.00% / [[267, 89], [79, 365]], * Val accuracy / confusion: 72.69% / [[144, 86], [56, 234]] ------------------------------ Epoch 313 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.317498 - Iter 024 / 025, Loss: 0.399983 * Train accuracy / confusion: 78.25% / [[265, 90], [84, 361]], * Val accuracy / confusion: 69.62% / [[137, 93], [65, 225]] ------------------------------ Epoch 314 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.730606 - Iter 024 / 025, Loss: 0.701779 * Train accuracy / confusion: 77.50% / [[258, 102], [78, 362]], * Val accuracy / confusion: 72.12% / [[141, 89], [56, 234]] ------------------------------ Epoch 315 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.485782 - Iter 024 / 025, Loss: 0.307705 * Train accuracy / confusion: 79.88% / [[272, 89], [72, 367]], * Val accuracy / confusion: 72.69% / [[149, 81], [61, 229]] ------------------------------ Epoch 316 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.476347 - Iter 024 / 025, Loss: 0.414646 * Train accuracy / confusion: 78.62% / [[265, 90], [81, 364]], * Val accuracy / confusion: 72.50% / [[149, 81], [62, 228]] ------------------------------ Epoch 317 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.644354 - Iter 024 / 025, Loss: 0.329999 * Train accuracy / confusion: 76.50% / [[258, 103], [85, 354]], * Val accuracy / confusion: 71.73% / [[141, 89], [58, 232]] ------------------------------ Epoch 318 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.497510 - Iter 024 / 025, Loss: 0.677110 * Train accuracy / confusion: 78.00% / [[266, 93], [83, 358]], * Val accuracy / confusion: 71.92% / [[142, 88], [58, 232]] ------------------------------ Epoch 319 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.599400 - Iter 024 / 025, Loss: 0.392086 * Train accuracy / confusion: 78.12% / [[263, 97], [78, 362]], * Val accuracy / confusion: 72.31% / [[145, 85], [59, 231]] ------------------------------ Epoch 320 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.536779 - Iter 024 / 025, Loss: 0.460417 * Train accuracy / confusion: 78.25% / [[262, 91], [83, 364]], * Val accuracy / confusion: 72.69% / [[142, 88], [54, 236]] ------------------------------ Epoch 321 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.352754 - Iter 024 / 025, Loss: 0.597828 * Train accuracy / confusion: 79.00% / [[267, 87], [81, 365]], * Val accuracy / confusion: 74.81% / [[151, 79], [52, 238]] ------------------------------ Epoch 322 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.612167 - Iter 024 / 025, Loss: 0.472849 * Train accuracy / confusion: 79.62% / [[267, 86], [77, 370]], * Val accuracy / confusion: 73.08% / [[148, 82], [58, 232]] ------------------------------ Epoch 323 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.355428 - Iter 024 / 025, Loss: 0.481112 * Train accuracy / confusion: 77.88% / [[256, 99], [78, 367]], * Val accuracy / confusion: 72.31% / [[136, 94], [50, 240]] ------------------------------ Epoch 324 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.347457 - Iter 024 / 025, Loss: 0.420397 * Train accuracy / confusion: 77.25% / [[260, 94], [88, 358]], * Val accuracy / confusion: 74.42% / [[149, 81], [52, 238]] ------------------------------ Epoch 325 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.591351 - Iter 024 / 025, Loss: 0.322224 * Train accuracy / confusion: 78.62% / [[262, 99], [72, 367]], * Val accuracy / confusion: 73.65% / [[150, 80], [57, 233]] ------------------------------ Epoch 326 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.441325 - Iter 024 / 025, Loss: 0.441045 * Train accuracy / confusion: 80.38% / [[272, 82], [75, 371]], * Val accuracy / confusion: 72.31% / [[146, 84], [60, 230]] ------------------------------ Epoch 327 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.587569 - Iter 024 / 025, Loss: 0.463741 * Train accuracy / confusion: 77.50% / [[257, 103], [77, 363]], * Val accuracy / confusion: 73.65% / [[145, 85], [52, 238]] ------------------------------ Epoch 328 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.727129 - Iter 024 / 025, Loss: 0.448245 * Train accuracy / confusion: 77.62% / [[254, 102], [77, 367]], * Val accuracy / confusion: 71.54% / [[144, 86], [62, 228]] ------------------------------ Epoch 329 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.508557 - Iter 024 / 025, Loss: 0.506303 * Train accuracy / confusion: 79.00% / [[261, 96], [72, 371]], * Val accuracy / confusion: 73.27% / [[156, 74], [65, 225]] ------------------------------ Epoch 330 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.534223 - Iter 024 / 025, Loss: 0.382203 * Train accuracy / confusion: 76.75% / [[252, 101], [85, 362]], * Val accuracy / confusion: 71.73% / [[142, 88], [59, 231]] ------------------------------ Epoch 331 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.706580 - Iter 024 / 025, Loss: 0.467468 * Train accuracy / confusion: 79.25% / [[271, 90], [76, 363]], * Val accuracy / confusion: 71.54% / [[145, 85], [63, 227]] ------------------------------ Epoch 332 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.483039 - Iter 024 / 025, Loss: 0.357727 * Train accuracy / confusion: 79.25% / [[271, 83], [83, 363]], * Val accuracy / confusion: 73.08% / [[144, 86], [54, 236]] ------------------------------ Epoch 333 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.386352 - Iter 024 / 025, Loss: 0.378650 * Train accuracy / confusion: 79.88% / [[264, 93], [68, 375]], * Val accuracy / confusion: 74.23% / [[145, 85], [49, 241]] ------------------------------ Epoch 334 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.387948 - Iter 024 / 025, Loss: 0.562350 * Train accuracy / confusion: 78.88% / [[259, 99], [70, 372]], * Val accuracy / confusion: 74.42% / [[149, 81], [52, 238]] ------------------------------ Epoch 335 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.460737 - Iter 024 / 025, Loss: 0.674098 * Train accuracy / confusion: 78.62% / [[268, 93], [78, 361]], * Val accuracy / confusion: 71.15% / [[144, 86], [64, 226]] ------------------------------ Epoch 336 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.495512 - Iter 024 / 025, Loss: 0.359007 * Train accuracy / confusion: 78.75% / [[265, 90], [80, 365]], * Val accuracy / confusion: 72.31% / [[147, 83], [61, 229]] ------------------------------ Epoch 337 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.337113 - Iter 024 / 025, Loss: 0.513518 * Train accuracy / confusion: 77.62% / [[254, 101], [78, 367]], * Val accuracy / confusion: 73.65% / [[146, 84], [53, 237]] ------------------------------ Epoch 338 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.621298 - Iter 024 / 025, Loss: 0.432515 * Train accuracy / confusion: 78.50% / [[258, 95], [77, 370]], * Val accuracy / confusion: 74.42% / [[153, 77], [56, 234]] ------------------------------ Epoch 339 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.569026 - Iter 024 / 025, Loss: 0.616432 * Train accuracy / confusion: 78.25% / [[262, 97], [77, 364]], * Val accuracy / confusion: 72.88% / [[152, 78], [63, 227]] ------------------------------ Epoch 340 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.496436 - Iter 024 / 025, Loss: 0.386157 * Train accuracy / confusion: 78.00% / [[252, 104], [72, 372]], * Val accuracy / confusion: 72.69% / [[146, 84], [58, 232]] ------------------------------ Epoch 341 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.496914 - Iter 024 / 025, Loss: 0.418547 * Train accuracy / confusion: 76.25% / [[249, 110], [80, 361]], * Val accuracy / confusion: 73.27% / [[145, 85], [54, 236]] ------------------------------ Epoch 342 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.414385 - Iter 024 / 025, Loss: 0.511398 * Train accuracy / confusion: 79.12% / [[270, 87], [80, 363]], * Val accuracy / confusion: 73.08% / [[150, 80], [60, 230]] ------------------------------ Epoch 343 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.363470 - Iter 024 / 025, Loss: 0.359475 * Train accuracy / confusion: 78.88% / [[263, 93], [76, 368]], * Val accuracy / confusion: 72.31% / [[143, 87], [57, 233]] ------------------------------ Epoch 344 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.538568 - Iter 024 / 025, Loss: 0.272833 * Train accuracy / confusion: 76.00% / [[255, 103], [89, 353]], * Val accuracy / confusion: 72.88% / [[140, 90], [51, 239]] ------------------------------ Epoch 345 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.362802 - Iter 024 / 025, Loss: 0.619721 * Train accuracy / confusion: 80.25% / [[270, 85], [73, 372]], * Val accuracy / confusion: 73.85% / [[146, 84], [52, 238]] ------------------------------ Epoch 346 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.420153 - Iter 024 / 025, Loss: 0.637362 * Train accuracy / confusion: 79.38% / [[269, 90], [75, 366]], * Val accuracy / confusion: 73.46% / [[148, 82], [56, 234]] ------------------------------ Epoch 347 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.439520 - Iter 024 / 025, Loss: 0.449049 * Train accuracy / confusion: 77.88% / [[266, 92], [85, 357]], * Val accuracy / confusion: 72.88% / [[150, 80], [61, 229]] ------------------------------ Epoch 348 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.293020 - Iter 024 / 025, Loss: 0.511709 * Train accuracy / confusion: 79.50% / [[265, 88], [76, 371]], * Val accuracy / confusion: 72.50% / [[150, 80], [63, 227]] ------------------------------ Epoch 349 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.302026 - Iter 024 / 025, Loss: 0.411694 * Train accuracy / confusion: 79.88% / [[270, 86], [75, 369]], * Val accuracy / confusion: 73.27% / [[141, 89], [50, 240]] ------------------------------ Epoch 350 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.449337 - Iter 024 / 025, Loss: 0.497408 * Train accuracy / confusion: 80.50% / [[269, 88], [68, 375]], * Val accuracy / confusion: 70.96% / [[135, 95], [56, 234]] ------------------------------ Epoch 351 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.483202 - Iter 024 / 025, Loss: 0.554953 * Train accuracy / confusion: 78.38% / [[261, 90], [83, 366]], * Val accuracy / confusion: 72.12% / [[141, 89], [56, 234]] ------------------------------ Epoch 352 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.414467 - Iter 024 / 025, Loss: 0.571253 * Train accuracy / confusion: 78.62% / [[256, 99], [72, 373]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 353 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466248 - Iter 024 / 025, Loss: 0.392106 * Train accuracy / confusion: 78.50% / [[267, 96], [76, 361]], * Val accuracy / confusion: 71.73% / [[145, 85], [62, 228]] ------------------------------ Epoch 354 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.368808 - Iter 024 / 025, Loss: 0.530750 * Train accuracy / confusion: 79.12% / [[265, 91], [76, 368]], * Val accuracy / confusion: 71.15% / [[144, 86], [64, 226]] ------------------------------ Epoch 355 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.557255 - Iter 024 / 025, Loss: 0.372020 * Train accuracy / confusion: 79.88% / [[261, 92], [69, 378]], * Val accuracy / confusion: 71.15% / [[141, 89], [61, 229]] ------------------------------ Epoch 356 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.343857 - Iter 024 / 025, Loss: 0.617643 * Train accuracy / confusion: 78.50% / [[267, 95], [77, 361]], * Val accuracy / confusion: 73.46% / [[147, 83], [55, 235]] ------------------------------ Epoch 357 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.386324 - Iter 024 / 025, Loss: 0.573519 * Train accuracy / confusion: 78.62% / [[265, 86], [85, 364]], * Val accuracy / confusion: 71.73% / [[141, 89], [58, 232]] ------------------------------ Epoch 358 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.454841 - Iter 024 / 025, Loss: 0.571452 * Train accuracy / confusion: 78.38% / [[266, 90], [83, 361]], * Val accuracy / confusion: 72.12% / [[144, 86], [59, 231]] ------------------------------ Epoch 359 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.482018 - Iter 024 / 025, Loss: 0.619023 * Train accuracy / confusion: 79.25% / [[264, 92], [74, 370]], * Val accuracy / confusion: 72.69% / [[142, 88], [54, 236]] ------------------------------ Epoch 360 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.382545 - Iter 024 / 025, Loss: 0.449839 * Train accuracy / confusion: 80.75% / [[268, 88], [66, 378]], * Val accuracy / confusion: 72.88% / [[142, 88], [53, 237]] ------------------------------ Epoch 361 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.565213 - Iter 024 / 025, Loss: 0.552184 * Train accuracy / confusion: 78.50% / [[269, 90], [82, 359]], * Val accuracy / confusion: 73.65% / [[151, 79], [58, 232]] ------------------------------ Epoch 362 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466704 - Iter 024 / 025, Loss: 0.599331 * Train accuracy / confusion: 76.62% / [[254, 100], [87, 359]], * Val accuracy / confusion: 74.23% / [[147, 83], [51, 239]] ------------------------------ Epoch 363 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.474080 - Iter 024 / 025, Loss: 0.541830 * Train accuracy / confusion: 79.50% / [[271, 88], [76, 365]], * Val accuracy / confusion: 72.50% / [[143, 87], [56, 234]] ------------------------------ Epoch 364 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.381739 - Iter 024 / 025, Loss: 0.605347 * Train accuracy / confusion: 79.38% / [[259, 97], [68, 376]], * Val accuracy / confusion: 73.46% / [[150, 80], [58, 232]] ------------------------------ Epoch 365 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.462433 - Iter 024 / 025, Loss: 0.396232 * Train accuracy / confusion: 81.75% / [[275, 84], [62, 379]], * Val accuracy / confusion: 71.73% / [[138, 92], [55, 235]] ------------------------------ Epoch 366 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.486707 - Iter 024 / 025, Loss: 0.492687 * Train accuracy / confusion: 80.00% / [[263, 95], [65, 377]], * Val accuracy / confusion: 73.46% / [[143, 87], [51, 239]] ------------------------------ Epoch 367 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.361731 - Iter 024 / 025, Loss: 0.332100 * Train accuracy / confusion: 78.50% / [[259, 91], [81, 369]], * Val accuracy / confusion: 70.77% / [[137, 93], [59, 231]] ------------------------------ Epoch 368 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.463905 - Iter 024 / 025, Loss: 0.310399 * Train accuracy / confusion: 79.25% / [[267, 91], [75, 367]], * Val accuracy / confusion: 71.73% / [[134, 96], [51, 239]] ------------------------------ Epoch 369 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.422972 - Iter 024 / 025, Loss: 0.576220 * Train accuracy / confusion: 80.25% / [[267, 88], [70, 375]], * Val accuracy / confusion: 72.31% / [[139, 91], [53, 237]] ------------------------------ Epoch 370 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.522109 - Iter 024 / 025, Loss: 0.410860 * Train accuracy / confusion: 77.50% / [[259, 101], [79, 361]], * Val accuracy / confusion: 71.73% / [[145, 85], [62, 228]] ------------------------------ Epoch 371 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.553717 - Iter 024 / 025, Loss: 0.337237 * Train accuracy / confusion: 79.88% / [[263, 90], [71, 376]], * Val accuracy / confusion: 70.58% / [[130, 100], [53, 237]] ------------------------------ Epoch 372 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.610200 - Iter 024 / 025, Loss: 0.343343 * Train accuracy / confusion: 78.00% / [[266, 93], [83, 358]], * Val accuracy / confusion: 71.92% / [[143, 87], [59, 231]] ------------------------------ Epoch 373 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.746371 - Iter 024 / 025, Loss: 0.430154 * Train accuracy / confusion: 78.12% / [[264, 93], [82, 361]], * Val accuracy / confusion: 73.65% / [[154, 76], [61, 229]] ------------------------------ Epoch 374 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.354046 - Iter 024 / 025, Loss: 0.556222 * Train accuracy / confusion: 78.50% / [[263, 89], [83, 365]], * Val accuracy / confusion: 72.88% / [[144, 86], [55, 235]] ------------------------------ Epoch 375 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.385667 - Iter 024 / 025, Loss: 0.476131 * Train accuracy / confusion: 79.12% / [[266, 93], [74, 367]], * Val accuracy / confusion: 72.31% / [[150, 80], [64, 226]] ------------------------------ Epoch 376 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.617932 - Iter 024 / 025, Loss: 0.500350 * Train accuracy / confusion: 78.00% / [[260, 100], [76, 364]], * Val accuracy / confusion: 72.12% / [[145, 85], [60, 230]] ------------------------------ Epoch 377 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.316371 - Iter 024 / 025, Loss: 0.510805 * Train accuracy / confusion: 78.62% / [[258, 96], [75, 371]], * Val accuracy / confusion: 73.27% / [[150, 80], [59, 231]] ------------------------------ Epoch 378 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.521030 - Iter 024 / 025, Loss: 0.440751 * Train accuracy / confusion: 78.38% / [[261, 91], [82, 366]], * Val accuracy / confusion: 70.00% / [[132, 98], [58, 232]] ------------------------------ Epoch 379 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.378590 - Iter 024 / 025, Loss: 0.381885 * Train accuracy / confusion: 77.88% / [[263, 96], [81, 360]], * Val accuracy / confusion: 74.62% / [[150, 80], [52, 238]] ------------------------------ Epoch 380 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.392633 - Iter 024 / 025, Loss: 0.393946 * Train accuracy / confusion: 80.88% / [[268, 88], [65, 379]], * Val accuracy / confusion: 71.54% / [[140, 90], [58, 232]] ------------------------------ Epoch 381 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.392993 - Iter 024 / 025, Loss: 0.493563 * Train accuracy / confusion: 79.25% / [[267, 93], [73, 367]], * Val accuracy / confusion: 71.35% / [[148, 82], [67, 223]] ------------------------------ Epoch 382 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.621195 - Iter 024 / 025, Loss: 0.461798 * Train accuracy / confusion: 78.00% / [[255, 98], [78, 369]], * Val accuracy / confusion: 72.69% / [[150, 80], [62, 228]] ------------------------------ Epoch 383 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.397329 - Iter 024 / 025, Loss: 0.510106 * Train accuracy / confusion: 77.00% / [[257, 102], [82, 359]], * Val accuracy / confusion: 70.58% / [[134, 96], [57, 233]] ------------------------------ Epoch 384 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.440366 - Iter 024 / 025, Loss: 0.643675 * Train accuracy / confusion: 80.38% / [[269, 88], [69, 374]], * Val accuracy / confusion: 73.08% / [[147, 83], [57, 233]] ------------------------------ Epoch 385 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.522522 - Iter 024 / 025, Loss: 0.420049 * Train accuracy / confusion: 78.25% / [[262, 93], [81, 364]], * Val accuracy / confusion: 73.85% / [[154, 76], [60, 230]] ------------------------------ Epoch 386 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.428773 - Iter 024 / 025, Loss: 0.457287 * Train accuracy / confusion: 80.62% / [[276, 81], [74, 369]], * Val accuracy / confusion: 71.73% / [[147, 83], [64, 226]] ------------------------------ Epoch 387 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.445166 - Iter 024 / 025, Loss: 0.361179 * Train accuracy / confusion: 79.00% / [[265, 95], [73, 367]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 388 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.359030 - Iter 024 / 025, Loss: 0.328262 * Train accuracy / confusion: 77.75% / [[263, 93], [85, 359]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 389 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.384716 - Iter 024 / 025, Loss: 0.554501 * Train accuracy / confusion: 78.12% / [[261, 92], [83, 364]], * Val accuracy / confusion: 72.50% / [[146, 84], [59, 231]] ------------------------------ Epoch 390 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.353909 - Iter 024 / 025, Loss: 0.432971 * Train accuracy / confusion: 79.50% / [[265, 92], [72, 371]], * Val accuracy / confusion: 70.38% / [[134, 96], [58, 232]] ------------------------------ Epoch 391 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.320775 - Iter 024 / 025, Loss: 0.354551 * Train accuracy / confusion: 78.50% / [[255, 101], [71, 373]], * Val accuracy / confusion: 71.54% / [[144, 86], [62, 228]] ------------------------------ Epoch 392 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.737188 - Iter 024 / 025, Loss: 0.613236 * Train accuracy / confusion: 81.50% / [[279, 81], [67, 373]], * Val accuracy / confusion: 69.62% / [[129, 101], [57, 233]] ------------------------------ Epoch 393 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.369043 - Iter 024 / 025, Loss: 0.443404 * Train accuracy / confusion: 79.12% / [[266, 96], [71, 367]], * Val accuracy / confusion: 70.38% / [[133, 97], [57, 233]] ------------------------------ Epoch 394 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.509552 - Iter 024 / 025, Loss: 0.388172 * Train accuracy / confusion: 78.00% / [[257, 100], [76, 367]], * Val accuracy / confusion: 71.92% / [[145, 85], [61, 229]] ------------------------------ Epoch 395 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.585757 - Iter 024 / 025, Loss: 0.359595 * Train accuracy / confusion: 81.62% / [[281, 80], [67, 372]], * Val accuracy / confusion: 73.08% / [[146, 84], [56, 234]] ------------------------------ Epoch 396 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.338261 - Iter 024 / 025, Loss: 0.442466 * Train accuracy / confusion: 79.62% / [[271, 88], [75, 366]], * Val accuracy / confusion: 71.35% / [[138, 92], [57, 233]] ------------------------------ Epoch 397 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.307349 - Iter 024 / 025, Loss: 0.482569 * Train accuracy / confusion: 80.25% / [[271, 87], [71, 371]], * Val accuracy / confusion: 72.88% / [[149, 81], [60, 230]] ------------------------------ Epoch 398 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.345345 - Iter 024 / 025, Loss: 0.522474 * Train accuracy / confusion: 81.38% / [[273, 84], [65, 378]], * Val accuracy / confusion: 70.96% / [[138, 92], [59, 231]] ------------------------------ Epoch 399 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.374696 - Iter 024 / 025, Loss: 0.454849 * Train accuracy / confusion: 79.25% / [[265, 93], [73, 369]], * Val accuracy / confusion: 72.12% / [[141, 89], [56, 234]] ------------------------------ Epoch 400 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.470791 - Iter 024 / 025, Loss: 0.478201 * Train accuracy / confusion: 79.12% / [[264, 89], [78, 369]], * Val accuracy / confusion: 73.08% / [[153, 77], [63, 227]] ------------------------------ Epoch 401 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.611435 - Iter 024 / 025, Loss: 0.311075 * Train accuracy / confusion: 79.88% / [[274, 85], [76, 365]], * Val accuracy / confusion: 71.73% / [[142, 88], [59, 231]] ------------------------------ Epoch 402 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.306357 - Iter 024 / 025, Loss: 0.336929 * Train accuracy / confusion: 80.50% / [[264, 93], [63, 380]], * Val accuracy / confusion: 74.23% / [[152, 78], [56, 234]] ------------------------------ Epoch 403 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.401023 - Iter 024 / 025, Loss: 0.456344 * Train accuracy / confusion: 77.75% / [[263, 93], [85, 359]], * Val accuracy / confusion: 71.92% / [[144, 86], [60, 230]] ------------------------------ Epoch 404 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.472976 - Iter 024 / 025, Loss: 0.295261 * Train accuracy / confusion: 80.50% / [[272, 80], [76, 372]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 405 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.386508 - Iter 024 / 025, Loss: 0.614031 * Train accuracy / confusion: 78.88% / [[264, 90], [79, 367]], * Val accuracy / confusion: 74.81% / [[159, 71], [60, 230]] ------------------------------ Epoch 406 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.337072 - Iter 024 / 025, Loss: 0.397241 * Train accuracy / confusion: 79.62% / [[266, 87], [76, 371]], * Val accuracy / confusion: 73.65% / [[154, 76], [61, 229]] ------------------------------ Epoch 407 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.622042 - Iter 024 / 025, Loss: 0.616766 * Train accuracy / confusion: 80.88% / [[272, 87], [66, 375]], * Val accuracy / confusion: 72.50% / [[141, 89], [54, 236]] ------------------------------ Epoch 408 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.382655 - Iter 024 / 025, Loss: 0.402380 * Train accuracy / confusion: 80.00% / [[270, 86], [74, 370]], * Val accuracy / confusion: 71.73% / [[146, 84], [63, 227]] ------------------------------ Epoch 409 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.435356 - Iter 024 / 025, Loss: 0.519041 * Train accuracy / confusion: 77.88% / [[252, 100], [77, 371]], * Val accuracy / confusion: 71.54% / [[146, 84], [64, 226]] ------------------------------ Epoch 410 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.353822 - Iter 024 / 025, Loss: 0.244697 * Train accuracy / confusion: 80.12% / [[269, 87], [72, 372]], * Val accuracy / confusion: 70.77% / [[146, 84], [68, 222]] ------------------------------ Epoch 411 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.582824 - Iter 024 / 025, Loss: 0.543493 * Train accuracy / confusion: 79.62% / [[269, 87], [76, 368]], * Val accuracy / confusion: 72.31% / [[139, 91], [53, 237]] ------------------------------ Epoch 412 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.401503 - Iter 024 / 025, Loss: 0.407558 * Train accuracy / confusion: 79.75% / [[268, 89], [73, 370]], * Val accuracy / confusion: 70.96% / [[135, 95], [56, 234]] ------------------------------ Epoch 413 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.456896 - Iter 024 / 025, Loss: 0.766260 * Train accuracy / confusion: 79.62% / [[269, 89], [74, 368]], * Val accuracy / confusion: 71.92% / [[138, 92], [54, 236]] ------------------------------ Epoch 414 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.552117 - Iter 024 / 025, Loss: 0.492992 * Train accuracy / confusion: 79.50% / [[270, 87], [77, 366]], * Val accuracy / confusion: 70.77% / [[138, 92], [60, 230]] ------------------------------ Epoch 415 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.354873 - Iter 024 / 025, Loss: 0.581326 * Train accuracy / confusion: 79.12% / [[263, 95], [72, 370]], * Val accuracy / confusion: 70.58% / [[138, 92], [61, 229]] ------------------------------ Epoch 416 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.385489 - Iter 024 / 025, Loss: 0.282259 * Train accuracy / confusion: 78.75% / [[266, 94], [76, 364]], * Val accuracy / confusion: 73.08% / [[149, 81], [59, 231]] ------------------------------ Epoch 417 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.259663 - Iter 024 / 025, Loss: 0.445720 * Train accuracy / confusion: 79.38% / [[273, 84], [81, 362]], * Val accuracy / confusion: 72.12% / [[144, 86], [59, 231]] ------------------------------ Epoch 418 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.523578 - Iter 024 / 025, Loss: 0.508554 * Train accuracy / confusion: 78.25% / [[261, 98], [76, 365]], * Val accuracy / confusion: 71.35% / [[137, 93], [56, 234]] ------------------------------ Epoch 419 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.392308 - Iter 024 / 025, Loss: 0.562352 * Train accuracy / confusion: 78.62% / [[261, 93], [78, 368]], * Val accuracy / confusion: 70.00% / [[124, 106], [50, 240]] ------------------------------ Epoch 420 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.360788 - Iter 024 / 025, Loss: 0.504857 * Train accuracy / confusion: 78.88% / [[268, 89], [80, 363]], * Val accuracy / confusion: 74.23% / [[144, 86], [48, 242]] ------------------------------ Epoch 421 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.396048 - Iter 024 / 025, Loss: 0.466079 * Train accuracy / confusion: 79.50% / [[269, 92], [72, 367]], * Val accuracy / confusion: 71.92% / [[138, 92], [54, 236]] ------------------------------ Epoch 422 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.453482 - Iter 024 / 025, Loss: 0.332144 * Train accuracy / confusion: 80.88% / [[262, 92], [61, 385]], * Val accuracy / confusion: 72.69% / [[146, 84], [58, 232]] ------------------------------ Epoch 423 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.451870 - Iter 024 / 025, Loss: 0.664028 * Train accuracy / confusion: 79.12% / [[266, 96], [71, 367]], * Val accuracy / confusion: 73.08% / [[144, 86], [54, 236]] ------------------------------ Epoch 424 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.664163 - Iter 024 / 025, Loss: 0.525942 * Train accuracy / confusion: 78.50% / [[259, 94], [78, 369]], * Val accuracy / confusion: 70.38% / [[138, 92], [62, 228]] ------------------------------ Epoch 425 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.505023 - Iter 024 / 025, Loss: 0.384601 * Train accuracy / confusion: 78.88% / [[268, 92], [77, 363]], * Val accuracy / confusion: 71.54% / [[137, 93], [55, 235]] ------------------------------ Epoch 426 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.361751 - Iter 024 / 025, Loss: 0.393559 * Train accuracy / confusion: 78.62% / [[265, 94], [77, 364]], * Val accuracy / confusion: 73.65% / [[147, 83], [54, 236]] ------------------------------ Epoch 427 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.494029 - Iter 024 / 025, Loss: 0.494976 * Train accuracy / confusion: 78.75% / [[257, 91], [79, 373]], * Val accuracy / confusion: 72.12% / [[142, 88], [57, 233]] ------------------------------ Epoch 428 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.350173 - Iter 024 / 025, Loss: 0.442509 * Train accuracy / confusion: 77.88% / [[259, 96], [81, 364]], * Val accuracy / confusion: 72.50% / [[141, 89], [54, 236]] ------------------------------ Epoch 429 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.466130 - Iter 024 / 025, Loss: 0.368985 * Train accuracy / confusion: 80.25% / [[271, 88], [70, 371]], * Val accuracy / confusion: 73.08% / [[143, 87], [53, 237]] ------------------------------ Epoch 430 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.256794 - Iter 024 / 025, Loss: 0.536494 * Train accuracy / confusion: 80.62% / [[271, 84], [71, 374]], * Val accuracy / confusion: 70.58% / [[141, 89], [64, 226]] ------------------------------ Epoch 431 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.390511 - Iter 024 / 025, Loss: 0.649827 * Train accuracy / confusion: 79.50% / [[267, 90], [74, 369]], * Val accuracy / confusion: 71.92% / [[132, 98], [48, 242]] ------------------------------ Epoch 432 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.474320 - Iter 024 / 025, Loss: 0.624732 * Train accuracy / confusion: 78.12% / [[257, 101], [74, 368]], * Val accuracy / confusion: 73.46% / [[142, 88], [50, 240]] ------------------------------ Epoch 433 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.282809 - Iter 024 / 025, Loss: 0.344613 * Train accuracy / confusion: 81.38% / [[272, 85], [64, 379]], * Val accuracy / confusion: 72.12% / [[141, 89], [56, 234]] ------------------------------ Epoch 434 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.335818 - Iter 024 / 025, Loss: 0.359290 * Train accuracy / confusion: 79.38% / [[269, 86], [79, 366]], * Val accuracy / confusion: 71.35% / [[138, 92], [57, 233]] ------------------------------ Epoch 435 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.369110 - Iter 024 / 025, Loss: 0.572186 * Train accuracy / confusion: 79.75% / [[268, 93], [69, 370]], * Val accuracy / confusion: 72.88% / [[143, 87], [54, 236]] ------------------------------ Epoch 436 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.454944 - Iter 024 / 025, Loss: 0.403057 * Train accuracy / confusion: 77.75% / [[257, 100], [78, 365]], * Val accuracy / confusion: 75.19% / [[149, 81], [48, 242]] ------------------------------ Epoch 437 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.455095 - Iter 024 / 025, Loss: 0.497702 * Train accuracy / confusion: 79.88% / [[270, 79], [82, 369]], * Val accuracy / confusion: 70.77% / [[136, 94], [58, 232]] ------------------------------ Epoch 438 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.313454 - Iter 024 / 025, Loss: 0.446674 * Train accuracy / confusion: 79.12% / [[262, 89], [78, 371]], * Val accuracy / confusion: 72.69% / [[149, 81], [61, 229]] ------------------------------ Epoch 439 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.327269 - Iter 024 / 025, Loss: 0.676058 * Train accuracy / confusion: 78.88% / [[269, 90], [79, 362]], * Val accuracy / confusion: 72.88% / [[144, 86], [55, 235]] ------------------------------ Epoch 440 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.448655 - Iter 024 / 025, Loss: 0.380887 * Train accuracy / confusion: 79.50% / [[268, 87], [77, 368]], * Val accuracy / confusion: 72.69% / [[142, 88], [54, 236]] ------------------------------ Epoch 441 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.315878 - Iter 024 / 025, Loss: 0.386162 * Train accuracy / confusion: 82.00% / [[277, 80], [64, 379]], * Val accuracy / confusion: 71.92% / [[135, 95], [51, 239]] ------------------------------ Epoch 442 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.326984 - Iter 024 / 025, Loss: 0.474480 * Train accuracy / confusion: 79.50% / [[260, 93], [71, 376]], * Val accuracy / confusion: 71.92% / [[149, 81], [65, 225]] ------------------------------ Epoch 443 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.509500 - Iter 024 / 025, Loss: 0.366302 * Train accuracy / confusion: 79.50% / [[264, 92], [72, 372]], * Val accuracy / confusion: 73.65% / [[143, 87], [50, 240]] ------------------------------ Epoch 444 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.555988 - Iter 024 / 025, Loss: 0.309177 * Train accuracy / confusion: 80.88% / [[273, 82], [71, 374]], * Val accuracy / confusion: 72.12% / [[136, 94], [51, 239]] ------------------------------ Epoch 445 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.646767 - Iter 024 / 025, Loss: 0.412250 * Train accuracy / confusion: 78.88% / [[268, 89], [80, 363]], * Val accuracy / confusion: 70.00% / [[141, 89], [67, 223]] ------------------------------ Epoch 446 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.284927 - Iter 024 / 025, Loss: 0.356477 * Train accuracy / confusion: 79.62% / [[270, 92], [71, 367]], * Val accuracy / confusion: 73.65% / [[148, 82], [55, 235]] ------------------------------ Epoch 447 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.352501 - Iter 024 / 025, Loss: 0.517483 * Train accuracy / confusion: 79.38% / [[271, 88], [77, 364]], * Val accuracy / confusion: 73.27% / [[146, 84], [55, 235]] ------------------------------ Epoch 448 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.410667 - Iter 024 / 025, Loss: 0.331700 * Train accuracy / confusion: 80.12% / [[268, 87], [72, 373]], * Val accuracy / confusion: 71.54% / [[141, 89], [59, 231]] ------------------------------ Epoch 449 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.271651 - Iter 024 / 025, Loss: 0.388721 * Train accuracy / confusion: 79.62% / [[276, 86], [77, 361]], * Val accuracy / confusion: 71.54% / [[148, 82], [66, 224]] ------------------------------ Epoch 450 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.407014 - Iter 024 / 025, Loss: 0.437356 * Train accuracy / confusion: 78.00% / [[268, 93], [83, 356]], * Val accuracy / confusion: 73.08% / [[140, 90], [50, 240]] ------------------------------ Epoch 451 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.611414 - Iter 024 / 025, Loss: 0.481934 * Train accuracy / confusion: 78.12% / [[257, 100], [75, 368]], * Val accuracy / confusion: 73.65% / [[150, 80], [57, 233]] ------------------------------ Epoch 452 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.449143 - Iter 024 / 025, Loss: 0.343780 * Train accuracy / confusion: 79.62% / [[270, 87], [76, 367]], * Val accuracy / confusion: 72.12% / [[145, 85], [60, 230]] ------------------------------ Epoch 453 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.465091 - Iter 024 / 025, Loss: 0.438727 * Train accuracy / confusion: 79.75% / [[268, 86], [76, 370]], * Val accuracy / confusion: 71.73% / [[141, 89], [58, 232]] ------------------------------ Epoch 454 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.514583 - Iter 024 / 025, Loss: 0.543573 * Train accuracy / confusion: 77.00% / [[253, 104], [80, 363]], * Val accuracy / confusion: 73.46% / [[146, 84], [54, 236]] ------------------------------ Epoch 455 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.289685 - Iter 024 / 025, Loss: 0.554946 * Train accuracy / confusion: 81.12% / [[274, 83], [68, 375]], * Val accuracy / confusion: 74.23% / [[149, 81], [53, 237]] ------------------------------ Epoch 456 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.621225 - Iter 024 / 025, Loss: 0.361424 * Train accuracy / confusion: 80.38% / [[267, 88], [69, 376]], * Val accuracy / confusion: 70.38% / [[130, 100], [54, 236]] ------------------------------ Epoch 457 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.520890 - Iter 024 / 025, Loss: 0.516041 * Train accuracy / confusion: 80.88% / [[271, 86], [67, 376]], * Val accuracy / confusion: 73.08% / [[138, 92], [48, 242]] ------------------------------ Epoch 458 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.541807 - Iter 024 / 025, Loss: 0.365136 * Train accuracy / confusion: 78.62% / [[264, 94], [77, 365]], * Val accuracy / confusion: 70.58% / [[134, 96], [57, 233]] ------------------------------ Epoch 459 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.436898 - Iter 024 / 025, Loss: 0.433555 * Train accuracy / confusion: 78.88% / [[269, 88], [81, 362]], * Val accuracy / confusion: 71.35% / [[145, 85], [64, 226]] ------------------------------ Epoch 460 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.453750 - Iter 024 / 025, Loss: 0.397358 * Train accuracy / confusion: 81.38% / [[277, 86], [63, 374]], * Val accuracy / confusion: 72.12% / [[147, 83], [62, 228]] ------------------------------ Epoch 461 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.325255 - Iter 024 / 025, Loss: 0.668112 * Train accuracy / confusion: 79.25% / [[271, 86], [80, 363]], * Val accuracy / confusion: 72.69% / [[139, 91], [51, 239]] ------------------------------ Epoch 462 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.375715 - Iter 024 / 025, Loss: 0.661361 * Train accuracy / confusion: 79.25% / [[271, 86], [80, 363]], * Val accuracy / confusion: 71.54% / [[142, 88], [60, 230]] ------------------------------ Epoch 463 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.438852 - Iter 024 / 025, Loss: 0.465610 * Train accuracy / confusion: 78.38% / [[260, 99], [74, 367]], * Val accuracy / confusion: 72.31% / [[147, 83], [61, 229]] ------------------------------ Epoch 464 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.388001 - Iter 024 / 025, Loss: 0.487496 * Train accuracy / confusion: 78.88% / [[262, 93], [76, 369]], * Val accuracy / confusion: 72.31% / [[149, 81], [63, 227]] ------------------------------ Epoch 465 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.564323 - Iter 024 / 025, Loss: 0.366039 * Train accuracy / confusion: 79.25% / [[267, 92], [74, 367]], * Val accuracy / confusion: 72.50% / [[139, 91], [52, 238]] ------------------------------ Epoch 466 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.457534 - Iter 024 / 025, Loss: 0.361089 * Train accuracy / confusion: 80.88% / [[274, 82], [71, 373]], * Val accuracy / confusion: 74.23% / [[149, 81], [53, 237]] ------------------------------ Epoch 467 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.370238 - Iter 024 / 025, Loss: 0.294113 * Train accuracy / confusion: 81.75% / [[273, 82], [64, 381]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 468 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.437225 - Iter 024 / 025, Loss: 0.308221 * Train accuracy / confusion: 79.88% / [[271, 85], [76, 368]], * Val accuracy / confusion: 72.50% / [[145, 85], [58, 232]] ------------------------------ Epoch 469 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.409793 - Iter 024 / 025, Loss: 0.338699 * Train accuracy / confusion: 80.88% / [[264, 90], [63, 383]], * Val accuracy / confusion: 74.81% / [[158, 72], [59, 231]] ------------------------------ Epoch 470 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.466869 - Iter 024 / 025, Loss: 0.454876 * Train accuracy / confusion: 81.50% / [[273, 81], [67, 379]], * Val accuracy / confusion: 70.96% / [[144, 86], [65, 225]] ------------------------------ Epoch 471 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.374258 - Iter 024 / 025, Loss: 0.256294 * Train accuracy / confusion: 80.25% / [[272, 87], [71, 370]], * Val accuracy / confusion: 72.12% / [[145, 85], [60, 230]] ------------------------------ Epoch 472 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.371387 - Iter 024 / 025, Loss: 0.529768 * Train accuracy / confusion: 80.00% / [[270, 88], [72, 370]], * Val accuracy / confusion: 73.65% / [[141, 89], [48, 242]] ------------------------------ Epoch 473 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.505911 - Iter 024 / 025, Loss: 0.314458 * Train accuracy / confusion: 79.00% / [[268, 90], [78, 364]], * Val accuracy / confusion: 73.08% / [[145, 85], [55, 235]] ------------------------------ Epoch 474 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.553594 - Iter 024 / 025, Loss: 0.413786 * Train accuracy / confusion: 79.88% / [[268, 85], [76, 371]], * Val accuracy / confusion: 72.12% / [[145, 85], [60, 230]] ------------------------------ Epoch 475 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.443920 - Iter 024 / 025, Loss: 0.498126 * Train accuracy / confusion: 80.00% / [[274, 84], [76, 366]], * Val accuracy / confusion: 70.96% / [[141, 89], [62, 228]] ------------------------------ Epoch 476 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.300335 - Iter 024 / 025, Loss: 0.577875 * Train accuracy / confusion: 78.50% / [[269, 94], [78, 359]], * Val accuracy / confusion: 71.35% / [[134, 96], [53, 237]] ------------------------------ Epoch 477 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.332673 - Iter 024 / 025, Loss: 0.276854 * Train accuracy / confusion: 80.88% / [[269, 88], [65, 378]], * Val accuracy / confusion: 72.31% / [[148, 82], [62, 228]] ------------------------------ Epoch 478 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.447665 - Iter 024 / 025, Loss: 0.377747 * Train accuracy / confusion: 79.12% / [[268, 83], [84, 365]], * Val accuracy / confusion: 73.08% / [[147, 83], [57, 233]] ------------------------------ Epoch 479 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.434059 - Iter 024 / 025, Loss: 0.375002 * Train accuracy / confusion: 80.25% / [[275, 89], [69, 367]], * Val accuracy / confusion: 72.88% / [[139, 91], [50, 240]] ------------------------------ Epoch 480 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.342156 - Iter 024 / 025, Loss: 0.452209 * Train accuracy / confusion: 79.88% / [[267, 90], [71, 372]], * Val accuracy / confusion: 70.00% / [[134, 96], [60, 230]] ------------------------------ Epoch 481 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.440504 - Iter 024 / 025, Loss: 0.510884 * Train accuracy / confusion: 80.12% / [[268, 87], [72, 373]], * Val accuracy / confusion: 70.77% / [[135, 95], [57, 233]] ------------------------------ Epoch 482 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.432397 - Iter 024 / 025, Loss: 0.336563 * Train accuracy / confusion: 79.62% / [[268, 87], [76, 369]], * Val accuracy / confusion: 72.50% / [[143, 87], [56, 234]] ------------------------------ Epoch 483 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.364033 - Iter 024 / 025, Loss: 0.472921 * Train accuracy / confusion: 80.00% / [[266, 88], [72, 374]], * Val accuracy / confusion: 71.92% / [[142, 88], [58, 232]] ------------------------------ Epoch 484 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.472525 - Iter 024 / 025, Loss: 0.603341 * Train accuracy / confusion: 79.88% / [[271, 89], [72, 368]], * Val accuracy / confusion: 72.31% / [[136, 94], [50, 240]] ------------------------------ Epoch 485 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.268459 - Iter 024 / 025, Loss: 0.362572 * Train accuracy / confusion: 81.75% / [[274, 85], [61, 380]], * Val accuracy / confusion: 74.23% / [[150, 80], [54, 236]] ------------------------------ Epoch 486 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.504976 - Iter 024 / 025, Loss: 0.468422 * Train accuracy / confusion: 80.50% / [[272, 84], [72, 372]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] ------------------------------ Epoch 487 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.409524 - Iter 024 / 025, Loss: 0.339610 * Train accuracy / confusion: 80.00% / [[265, 90], [70, 375]], * Val accuracy / confusion: 70.77% / [[139, 91], [61, 229]] ------------------------------ Epoch 488 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.299118 - Iter 024 / 025, Loss: 0.504665 * Train accuracy / confusion: 78.75% / [[262, 93], [77, 368]], * Val accuracy / confusion: 73.27% / [[155, 75], [64, 226]] ------------------------------ Epoch 489 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.540986 - Iter 024 / 025, Loss: 0.331326 * Train accuracy / confusion: 79.38% / [[264, 90], [75, 371]], * Val accuracy / confusion: 73.08% / [[143, 87], [53, 237]] ------------------------------ Epoch 490 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.415924 - Iter 024 / 025, Loss: 0.549682 * Train accuracy / confusion: 77.75% / [[266, 93], [85, 356]], * Val accuracy / confusion: 72.88% / [[143, 87], [54, 236]] ------------------------------ Epoch 491 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.617337 - Iter 024 / 025, Loss: 0.531770 * Train accuracy / confusion: 80.50% / [[265, 84], [72, 379]], * Val accuracy / confusion: 74.23% / [[153, 77], [57, 233]] ------------------------------ Epoch 492 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.378071 - Iter 024 / 025, Loss: 0.339245 * Train accuracy / confusion: 81.25% / [[273, 85], [65, 377]], * Val accuracy / confusion: 72.50% / [[143, 87], [56, 234]] ------------------------------ Epoch 493 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.436825 - Iter 024 / 025, Loss: 0.543646 * Train accuracy / confusion: 80.88% / [[273, 82], [71, 374]], * Val accuracy / confusion: 71.35% / [[140, 90], [59, 231]] ------------------------------ Epoch 494 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.443070 - Iter 024 / 025, Loss: 0.364779 * Train accuracy / confusion: 79.38% / [[261, 94], [71, 374]], * Val accuracy / confusion: 70.77% / [[140, 90], [62, 228]] ------------------------------ Epoch 495 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.302538 - Iter 024 / 025, Loss: 0.372654 * Train accuracy / confusion: 80.00% / [[267, 86], [74, 373]], * Val accuracy / confusion: 71.92% / [[140, 90], [56, 234]] ------------------------------ Epoch 496 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.400529 - Iter 024 / 025, Loss: 0.533864 * Train accuracy / confusion: 77.50% / [[265, 93], [87, 355]], * Val accuracy / confusion: 70.96% / [[134, 96], [55, 235]] ------------------------------ Epoch 497 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.504326 - Iter 024 / 025, Loss: 0.566862 * Train accuracy / confusion: 78.00% / [[252, 101], [75, 372]], * Val accuracy / confusion: 72.12% / [[150, 80], [65, 225]] ------------------------------ Epoch 498 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.449807 - Iter 024 / 025, Loss: 0.399036 * Train accuracy / confusion: 79.25% / [[280, 80], [86, 354]], * Val accuracy / confusion: 70.38% / [[135, 95], [59, 231]] ------------------------------ Epoch 499 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.318871 - Iter 024 / 025, Loss: 0.592348 * Train accuracy / confusion: 79.38% / [[263, 88], [77, 372]], * Val accuracy / confusion: 73.08% / [[141, 89], [51, 239]] ------------------------------ Epoch 500 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.464132 - Iter 024 / 025, Loss: 0.596579 * Train accuracy / confusion: 78.75% / [[262, 95], [75, 368]], * Val accuracy / confusion: 71.35% / [[141, 89], [60, 230]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 72.88% - Confusion matrix (last model): [[ 942 468] [ 378 1332]]
- Test accuracy (best model): 71.54% - Confusion matrix (best model): [[ 992 418] [ 470 1240]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_M5_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '00299': {'GT': 0, 'Acc': ' 10.00%', 'Pred': [3, 27], 'edfname': '00671212_160819'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'01026': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01225123_050815'},
'00176': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00602435_270217'},
'00591': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '00896386_240914'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00811': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '01116389_271118'},
'01235': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01336270_040717'},
'00835': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01134450_140519'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'00719': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01006707_260319'},
'00495': {'GT': 1, 'Acc': ' 46.67%', 'Pred': [16, 14], 'edfname': '00805584_090819'},
'00862': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139924_300315'},
'00913': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '01151967_160414'},
'00097': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00372136_181214'},
'00122': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00416942_190516'},
'00439': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00760780_141118'},
'01378': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01432133_160519'},
'00705': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00986061_270116'},
'00212': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00617893_231018'},
'01105': {'GT': 0, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01266696_110516'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'00531': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00840844_250119'},
'00192': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00608961_131118'},
'00643': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00948785_120116'},
'01177': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01300390_251116'},
'01209': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01318352_281118'},
'00341': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695058_191017'},
'00357': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00707209_261219'},
'00527': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00840062_080519'},
'01307': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '01376302_060718'},
'00058': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '00285244_020414'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00508': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00817022_010415'},
'00021': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00141670_081217'},
'00408': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '00740750_110315'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'01330': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01392885_240718'},
'00329': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '00685248_150414'},
'00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
'00900': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01147100'},
'00700': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '00985401_011117'},
'00584': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00891889_060717'},
'01066': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '01242983_071215'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00369252_131216'},
'01165': {'GT': 0, 'Acc': ' 63.33%', 'Pred': [19, 11], 'edfname': '01296533_281116'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00030': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_230317'},
'01123': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '01276165_040117'},
'00982': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01200248_290120'},
'00917': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01154159_230414'},
'00255': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00645911_021115'},
'01039': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01235034_290120'},
'00961': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01182545_070316'},
'00338': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00692685_200919'},
'00346': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '00698358_020916'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'00704': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_240215'},
'00125': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '00418981_090316'},
'00859': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139924_060417'},
'00471': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00784417_100315'},
'00498': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00809366_050116'},
'01239': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01338557_190717'},
'00481': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00796686_020819'},
'00369': {'GT': 1, 'Acc': ' 20.00%', 'Pred': [24, 6], 'edfname': '00715828_111016'},
'01281': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01358607_280918'},
'01360': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01415643_150119'},
'01288': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01364379_260919'},
'00885': {'GT': 0, 'Acc': ' 36.67%', 'Pred': [11, 19], 'edfname': '01142810_180214'},
'00858': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139894_140214'},
'01138': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '01281605_070716'},
'00821': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01128393_300715'},
'00870': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01139947_120214'},
'01215': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01321744_130417'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00464': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00779318_101117'},
'00923': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01155730_070514'},
'00815': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '01125477_030918'},
'01287': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01364379_230118'},
'01160': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '01295899_041016'},
'00104': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '00395714_170915'},
'01353': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01410438_241218'},
'01267': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01351393_111119'},
'01156': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01293646_120719'},
'00504': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
'01045': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01235281_191015'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00094': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00366974_061118'},
'00741': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01025734_280715'},
'00303': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00672867_031116'},
'00156': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00502785_041019'},
'00851': {'GT': 0, 'Acc': ' 36.67%', 'Pred': [11, 19], 'edfname': '01138297_230114'},
'00730': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01011922_270815'},
'00343': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695272_100519'},
'00756': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '01035162_180119'},
'01232': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01335435_121119'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00588': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00895530_090616'},
'00076': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00317645_311016'},
'00653': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00952170_060516'}}
class BasicResBlock(nn.Module):
expansion: int = 1
def __init__(self, c_in, c_out, kernel_size, stride) -> None:
super().__init__()
self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=c_out,
kernel_size=kernel_size, stride=stride,
padding=kernel_size//2, bias=False)
self.bn1 = nn.BatchNorm1d(c_out)
self.conv2 = nn.Conv1d(in_channels=c_out, out_channels=c_out,
kernel_size=kernel_size, stride=1,
padding=kernel_size//2, bias=False)
self.bn2 = nn.BatchNorm1d(c_out)
self.relu = nn.ReLU(inplace=True)
self.downsample = None
if stride != 1 or c_in != c_out:
self.downsample = nn.Sequential(
nn.Conv1d(in_channels=c_in, out_channels=c_out,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm1d(c_out)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
identity = x
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
if self.downsample is not None:
identity = self.downsample(identity)
x = self.relu(x + identity)
return x
class BottleneckBlock(nn.Module):
expansion: int = 4
def __init__(self, c_in, c_out, kernel_size, stride) -> None:
super().__init__()
width = c_out
self.conv1 = nn.Conv1d(in_channels=c_in, out_channels=width,
kernel_size=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm1d(width)
self.conv2 = nn.Conv1d(in_channels=width, out_channels=width,
kernel_size=kernel_size, stride=stride,
padding=kernel_size//2, bias=False)
self.bn2 = nn.BatchNorm1d(width)
self.conv3 = nn.Conv1d(in_channels=width, out_channels=c_out*self.expansion,
kernel_size=1, stride=1, bias=False)
self.bn3 = nn.BatchNorm1d(c_out*self.expansion)
self.relu = nn.ReLU(inplace=True)
self.downsample = None
if stride != 1 or c_in != c_out*self.expansion:
self.downsample = nn.Sequential(
nn.Conv1d(in_channels=c_in, out_channels=c_out*self.expansion,
kernel_size=1, stride=stride, bias=False),
nn.BatchNorm1d(c_out*self.expansion)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
identity = x
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
x = self.relu(x)
x = self.conv3(x)
x = self.bn3(x)
if self.downsample is not None:
identity = self.downsample(identity)
x = self.relu(x + identity)
return x
class ResNet(nn.Module):
def __init__(self,
block: Type[Union[BasicResBlock, BottleneckBlock]],
conv_layers: List[int],
n_fc: int,
n_input=20,
n_output=3,
n_start=64,
kernel_size=9,
use_age=True,
final_pool='average') -> None:
super().__init__()
if final_pool not in {'average', 'max'}:
raise ValueError("final_pool must be set to one of ['average', 'max']")
self.c_current = n_start
self.use_age = use_age
self.input_stage = nn.Sequential(
nn.Conv1d(in_channels=n_input, out_channels=n_start,
kernel_size=kernel_size*3, stride=2,
padding=(kernel_size*3)//2, bias=False),
nn.BatchNorm1d(n_start),
nn.ReLU(),
)
self.conv_stage1 = self._make_conv_layer(block, conv_layers[0], n_start, kernel_size, stride=3)
self.conv_stage2 = self._make_conv_layer(block, conv_layers[1], n_start*2, kernel_size, stride=3)
self.conv_stage3 = self._make_conv_layer(block, conv_layers[2], n_start*4, kernel_size, stride=3)
self.conv_stage4 = self._make_conv_layer(block, conv_layers[3], n_start*8, kernel_size, stride=3)
if final_pool == 'average':
self.final_pool = nn.AdaptiveAvgPool1d(1)
elif final_pool == 'max':
self.final_pool = nn.AdaptiveMaxPool1d(1)
fc_layers = []
if self.use_age:
self.c_current = self.c_current + 1
for l in range(n_fc):
layer = nn.Sequential(nn.Linear(self.c_current, self.c_current // 2, bias=False),
nn.Dropout(p=0.1),
nn.BatchNorm1d(self.c_current // 2),
nn.ReLU())
self.c_current = self.c_current // 2
fc_layers.append(layer)
fc_layers.append(nn.Linear(self.c_current, n_output))
self.fc_stage = nn.Sequential(*fc_layers)
def reset_weights(self):
for m in self.modules():
if hasattr(m, 'reset_parameters'):
m.reset_parameters()
def _make_conv_layer(self, block: Type[Union[BasicResBlock, BottleneckBlock]],
n_block: int, c_out: int, kernel_size: int, stride: int = 1) -> nn.Sequential:
layers = []
c_in = self.c_current
layers.append(block(c_in, c_out, kernel_size, stride=1))
c_in = c_out * block.expansion
self.c_current = c_in
for _ in range(1, n_block):
layers.append(block(c_in, c_out, kernel_size, stride=1))
layers.append(nn.MaxPool1d(kernel_size=stride))
return nn.Sequential(*layers)
def forward(self, x, age, print_shape=False):
x = self.input_stage(x)
x = self.conv_stage1(x)
x = self.conv_stage2(x)
x = self.conv_stage3(x)
x = self.conv_stage4(x)
if print_shape:
print('Shape right before squeezing:', x.shape)
x = self.final_pool(x).squeeze()
if self.use_age:
x = torch.cat((x, age.reshape(-1, 1)), dim=1)
x = self.fc_stage(x)
return x
# return F.log_softmax(x, dim=2)
model = ResNet(block=BottleneckBlock,
conv_layers=[2, 2, 2, 2],
n_fc=3,
n_input=train_dataset[0]['signal'].shape[0],
n_output=2,
n_start=64,
kernel_size=9,
use_age=True,
final_pool='max')
model = model.to(device, dtype=torch.float32)
print(model)
print()
# tensorboard visualization
visualize_network_tensorboard(model, 'ResNet-like')
# number of parameters
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
ResNet(
(input_stage): Sequential(
(0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
(1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU()
)
(conv_stage1): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(256, 64, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage2): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(256, 128, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage3): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(512, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(512, 1024, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(1024, 256, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage4): Sequential(
(0): BottleneckBlock(
(conv1): Conv1d(1024, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(1024, 2048, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): BottleneckBlock(
(conv1): Conv1d(2048, 512, kernel_size=(1,), stride=(1,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
(bn3): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(final_pool): AdaptiveMaxPool1d(output_size=1)
(fc_stage): Sequential(
(0): Sequential(
(0): Linear(in_features=2049, out_features=1024, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(1): Sequential(
(0): Linear(in_features=1024, out_features=512, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(2): Sequential(
(0): Linear(in_features=512, out_features=256, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(3): Linear(in_features=256, out_features=2, bias=True)
)
)
Shape right before squeezing: torch.Size([32, 2048, 12])
The Number of parameters of the model: 16,728,962
# record = learning_rate_search(model,
# min_log_lr=-4.5,
# max_log_lr=-1.4,
# trials=300,
# epochs=1)
# draw_learning_rate_record(record)
# best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
best_log_lr = -3.0
print('best_log_lr:', best_log_lr)
best_log_lr: -3.0
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.736125 - Iter 024 / 025, Loss: 0.789995 * Train accuracy / confusion: 50.25% / [[117, 237], [161, 285]], * Val accuracy / confusion: 45.58% / [[187, 43], [240, 50]] ------------------------------ Epoch 002 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.750136 - Iter 024 / 025, Loss: 0.673220 * Train accuracy / confusion: 50.75% / [[75, 283], [111, 331]], * Val accuracy / confusion: 50.77% / [[153, 77], [179, 111]] ------------------------------ Epoch 003 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.681690 - Iter 024 / 025, Loss: 0.661992 * Train accuracy / confusion: 52.75% / [[30, 327], [51, 392]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 004 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.658896 - Iter 024 / 025, Loss: 0.683558 * Train accuracy / confusion: 55.12% / [[72, 286], [73, 369]], * Val accuracy / confusion: 54.62% / [[21, 209], [27, 263]] ------------------------------ Epoch 005 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.665527 - Iter 024 / 025, Loss: 0.691935 * Train accuracy / confusion: 53.50% / [[44, 310], [62, 384]], * Val accuracy / confusion: 57.31% / [[31, 199], [23, 267]] ------------------------------ Epoch 006 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.796580 - Iter 024 / 025, Loss: 0.706201 * Train accuracy / confusion: 54.62% / [[42, 313], [50, 395]], * Val accuracy / confusion: 53.65% / [[68, 162], [79, 211]] ------------------------------ Epoch 007 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.684664 - Iter 024 / 025, Loss: 0.721899 * Train accuracy / confusion: 54.88% / [[73, 285], [76, 366]], * Val accuracy / confusion: 55.58% / [[61, 169], [62, 228]] ------------------------------ Epoch 008 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.699762 - Iter 024 / 025, Loss: 0.674397 * Train accuracy / confusion: 51.50% / [[72, 286], [102, 340]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 009 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.693135 - Iter 024 / 025, Loss: 0.744589 * Train accuracy / confusion: 54.75% / [[27, 329], [33, 411]], * Val accuracy / confusion: 55.96% / [[1, 229], [0, 290]] ------------------------------ Epoch 010 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.720662 - Iter 024 / 025, Loss: 0.744414 * Train accuracy / confusion: 52.88% / [[104, 255], [122, 319]], * Val accuracy / confusion: 51.54% / [[152, 78], [174, 116]] ------------------------------ Epoch 011 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.648790 - Iter 024 / 025, Loss: 0.734341 * Train accuracy / confusion: 53.88% / [[31, 326], [43, 400]], * Val accuracy / confusion: 56.15% / [[78, 152], [76, 214]] ------------------------------ Epoch 012 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.689460 - Iter 024 / 025, Loss: 0.710297 * Train accuracy / confusion: 52.12% / [[76, 280], [103, 341]], * Val accuracy / confusion: 52.88% / [[34, 196], [49, 241]] ------------------------------ Epoch 013 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.665264 - Iter 024 / 025, Loss: 0.747374 * Train accuracy / confusion: 52.00% / [[66, 289], [95, 350]], * Val accuracy / confusion: 56.15% / [[23, 207], [21, 269]] ------------------------------ Epoch 014 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.788353 - Iter 024 / 025, Loss: 0.659979 * Train accuracy / confusion: 52.88% / [[29, 334], [43, 394]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 015 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.761137 - Iter 024 / 025, Loss: 0.687563 * Train accuracy / confusion: 52.62% / [[28, 326], [53, 393]], * Val accuracy / confusion: 55.19% / [[22, 208], [25, 265]] ------------------------------ Epoch 016 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.714828 - Iter 024 / 025, Loss: 0.686498 * Train accuracy / confusion: 54.88% / [[15, 342], [19, 424]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 017 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.684375 - Iter 024 / 025, Loss: 0.699209 * Train accuracy / confusion: 53.88% / [[13, 344], [25, 418]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 018 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.690537 - Iter 024 / 025, Loss: 0.735628 * Train accuracy / confusion: 55.88% / [[19, 332], [21, 428]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 019 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.670803 - Iter 024 / 025, Loss: 0.672954 * Train accuracy / confusion: 55.50% / [[44, 309], [47, 400]], * Val accuracy / confusion: 55.19% / [[1, 229], [4, 286]] ------------------------------ Epoch 020 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.712291 - Iter 024 / 025, Loss: 0.643588 * Train accuracy / confusion: 54.38% / [[66, 291], [74, 369]], * Val accuracy / confusion: 56.15% / [[2, 228], [0, 290]] ------------------------------ Epoch 021 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.678242 - Iter 024 / 025, Loss: 0.741889 * Train accuracy / confusion: 55.50% / [[15, 341], [15, 429]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 022 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.678367 - Iter 024 / 025, Loss: 0.665185 * Train accuracy / confusion: 55.38% / [[38, 318], [39, 405]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 023 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.696462 - Iter 024 / 025, Loss: 0.700791 * Train accuracy / confusion: 53.50% / [[65, 296], [76, 363]], * Val accuracy / confusion: 55.38% / [[52, 178], [54, 236]] ------------------------------ Epoch 024 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.742937 - Iter 024 / 025, Loss: 0.692255 * Train accuracy / confusion: 53.88% / [[33, 325], [44, 398]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 025 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.711370 - Iter 024 / 025, Loss: 0.664707 * Train accuracy / confusion: 54.62% / [[38, 312], [51, 399]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 026 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.646408 - Iter 024 / 025, Loss: 0.702456 * Train accuracy / confusion: 55.50% / [[49, 302], [54, 395]], * Val accuracy / confusion: 55.77% / [[0, 230], [0, 290]] ------------------------------ Epoch 027 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.644685 - Iter 024 / 025, Loss: 0.686412 * Train accuracy / confusion: 58.62% / [[131, 227], [104, 338]], * Val accuracy / confusion: 56.54% / [[7, 223], [3, 287]] ------------------------------ Epoch 028 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.698203 - Iter 024 / 025, Loss: 0.678013 * Train accuracy / confusion: 56.12% / [[48, 303], [48, 401]], * Val accuracy / confusion: 50.38% / [[115, 115], [143, 147]] ------------------------------ Epoch 029 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.701334 - Iter 024 / 025, Loss: 0.717005 * Train accuracy / confusion: 54.38% / [[11, 345], [20, 424]], * Val accuracy / confusion: 53.46% / [[63, 167], [75, 215]] ------------------------------ Epoch 030 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.682525 - Iter 024 / 025, Loss: 0.694393 * Train accuracy / confusion: 56.38% / [[47, 312], [37, 404]], * Val accuracy / confusion: 55.96% / [[1, 229], [0, 290]] ------------------------------ Epoch 031 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.730053 - Iter 024 / 025, Loss: 0.714647 * Train accuracy / confusion: 54.12% / [[39, 319], [48, 394]], * Val accuracy / confusion: 57.31% / [[9, 221], [1, 289]] ------------------------------ Epoch 032 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.612550 - Iter 024 / 025, Loss: 0.747740 * Train accuracy / confusion: 56.38% / [[142, 214], [135, 309]], * Val accuracy / confusion: 56.15% / [[39, 191], [37, 253]] ------------------------------ Epoch 033 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.704364 - Iter 024 / 025, Loss: 0.699315 * Train accuracy / confusion: 55.75% / [[63, 292], [62, 383]], * Val accuracy / confusion: 59.62% / [[158, 72], [138, 152]] ------------------------------ Epoch 034 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.673105 - Iter 024 / 025, Loss: 0.752600 * Train accuracy / confusion: 56.38% / [[158, 200], [149, 293]], * Val accuracy / confusion: 61.92% / [[124, 106], [92, 198]] ------------------------------ Epoch 035 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.607431 - Iter 024 / 025, Loss: 0.629204 * Train accuracy / confusion: 58.12% / [[148, 207], [128, 317]], * Val accuracy / confusion: 58.46% / [[49, 181], [35, 255]] ------------------------------ Epoch 036 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.720296 - Iter 024 / 025, Loss: 0.619064 * Train accuracy / confusion: 61.25% / [[175, 183], [127, 315]], * Val accuracy / confusion: 59.62% / [[92, 138], [72, 218]] ------------------------------ Epoch 037 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.682728 - Iter 024 / 025, Loss: 0.639227 * Train accuracy / confusion: 56.88% / [[203, 151], [194, 252]], * Val accuracy / confusion: 58.46% / [[50, 180], [36, 254]] ------------------------------ Epoch 038 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.687879 - Iter 024 / 025, Loss: 0.595478 * Train accuracy / confusion: 61.88% / [[204, 151], [154, 291]], * Val accuracy / confusion: 61.92% / [[91, 139], [59, 231]] ------------------------------ Epoch 039 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.710517 - Iter 024 / 025, Loss: 0.696281 * Train accuracy / confusion: 60.88% / [[163, 194], [119, 324]], * Val accuracy / confusion: 61.15% / [[68, 162], [40, 250]] ------------------------------ Epoch 040 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.695353 - Iter 024 / 025, Loss: 0.638851 * Train accuracy / confusion: 61.00% / [[186, 171], [141, 302]], * Val accuracy / confusion: 63.27% / [[119, 111], [80, 210]] ------------------------------ Epoch 041 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.612626 - Iter 024 / 025, Loss: 0.657153 * Train accuracy / confusion: 60.88% / [[195, 159], [154, 292]], * Val accuracy / confusion: 59.23% / [[57, 173], [39, 251]] ------------------------------ Epoch 042 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.641921 - Iter 024 / 025, Loss: 0.578147 * Train accuracy / confusion: 60.75% / [[206, 153], [161, 280]], * Val accuracy / confusion: 64.42% / [[102, 128], [57, 233]] ------------------------------ Epoch 043 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.642527 - Iter 024 / 025, Loss: 0.580369 * Train accuracy / confusion: 62.38% / [[206, 149], [152, 293]], * Val accuracy / confusion: 62.88% / [[184, 46], [147, 143]] ------------------------------ Epoch 044 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.649678 - Iter 024 / 025, Loss: 0.598897 * Train accuracy / confusion: 64.12% / [[207, 152], [135, 306]], * Val accuracy / confusion: 61.54% / [[96, 134], [66, 224]] ------------------------------ Epoch 045 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.672084 - Iter 024 / 025, Loss: 0.726102 * Train accuracy / confusion: 64.50% / [[207, 151], [133, 309]], * Val accuracy / confusion: 60.19% / [[212, 18], [189, 101]] ------------------------------ Epoch 046 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.631588 - Iter 024 / 025, Loss: 0.608534 * Train accuracy / confusion: 65.38% / [[221, 136], [141, 302]], * Val accuracy / confusion: 59.62% / [[80, 150], [60, 230]] ------------------------------ Epoch 047 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.759357 - Iter 024 / 025, Loss: 0.647624 * Train accuracy / confusion: 61.38% / [[159, 199], [110, 332]], * Val accuracy / confusion: 61.92% / [[185, 45], [153, 137]] ------------------------------ Epoch 048 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.651492 - Iter 024 / 025, Loss: 0.682565 * Train accuracy / confusion: 64.62% / [[224, 136], [147, 293]], * Val accuracy / confusion: 67.88% / [[118, 112], [55, 235]] ------------------------------ Epoch 049 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.654087 - Iter 024 / 025, Loss: 0.676687 * Train accuracy / confusion: 65.75% / [[205, 154], [120, 321]], * Val accuracy / confusion: 60.96% / [[112, 118], [85, 205]] ------------------------------ Epoch 050 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.611856 - Iter 024 / 025, Loss: 0.552111 * Train accuracy / confusion: 66.12% / [[217, 138], [133, 312]], * Val accuracy / confusion: 60.96% / [[205, 25], [178, 112]] ------------------------------ Epoch 051 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.619423 - Iter 024 / 025, Loss: 0.631538 * Train accuracy / confusion: 69.00% / [[231, 126], [122, 321]], * Val accuracy / confusion: 70.58% / [[176, 54], [99, 191]] ------------------------------ Epoch 052 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.690348 - Iter 024 / 025, Loss: 0.747123 * Train accuracy / confusion: 64.75% / [[189, 168], [114, 329]], * Val accuracy / confusion: 62.12% / [[73, 157], [40, 250]] ------------------------------ Epoch 053 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517799 - Iter 024 / 025, Loss: 0.639871 * Train accuracy / confusion: 67.62% / [[195, 158], [101, 346]], * Val accuracy / confusion: 70.38% / [[137, 93], [61, 229]] ------------------------------ Epoch 054 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.545568 - Iter 024 / 025, Loss: 0.567030 * Train accuracy / confusion: 67.38% / [[205, 151], [110, 334]], * Val accuracy / confusion: 65.00% / [[82, 148], [34, 256]] ------------------------------ Epoch 055 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519129 - Iter 024 / 025, Loss: 0.545916 * Train accuracy / confusion: 70.12% / [[224, 128], [111, 337]], * Val accuracy / confusion: 64.23% / [[54, 176], [10, 280]] ------------------------------ Epoch 056 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.573434 - Iter 024 / 025, Loss: 0.522595 * Train accuracy / confusion: 70.12% / [[220, 138], [101, 341]], * Val accuracy / confusion: 68.65% / [[95, 135], [28, 262]] ------------------------------ Epoch 057 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.449657 - Iter 024 / 025, Loss: 0.764550 * Train accuracy / confusion: 68.88% / [[221, 136], [113, 330]], * Val accuracy / confusion: 62.12% / [[211, 19], [178, 112]] ------------------------------ Epoch 058 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.561077 - Iter 024 / 025, Loss: 0.820319 * Train accuracy / confusion: 67.88% / [[213, 147], [110, 330]], * Val accuracy / confusion: 70.19% / [[111, 119], [36, 254]] ------------------------------ Epoch 059 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.616690 - Iter 024 / 025, Loss: 0.522591 * Train accuracy / confusion: 70.00% / [[223, 132], [108, 337]], * Val accuracy / confusion: 71.92% / [[133, 97], [49, 241]] ------------------------------ Epoch 060 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.589230 - Iter 024 / 025, Loss: 0.509165 * Train accuracy / confusion: 70.50% / [[216, 137], [99, 348]], * Val accuracy / confusion: 68.08% / [[102, 128], [38, 252]] ------------------------------ Epoch 061 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.587805 - Iter 024 / 025, Loss: 0.621712 * Train accuracy / confusion: 71.12% / [[221, 137], [94, 348]], * Val accuracy / confusion: 68.46% / [[167, 63], [101, 189]] ------------------------------ Epoch 062 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.565941 - Iter 024 / 025, Loss: 0.703641 * Train accuracy / confusion: 70.88% / [[250, 105], [128, 317]], * Val accuracy / confusion: 71.15% / [[165, 65], [85, 205]] ------------------------------ Epoch 063 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.455007 - Iter 024 / 025, Loss: 0.533656 * Train accuracy / confusion: 72.38% / [[254, 103], [118, 325]], * Val accuracy / confusion: 70.96% / [[174, 56], [95, 195]] ------------------------------ Epoch 064 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.642295 - Iter 024 / 025, Loss: 0.530700 * Train accuracy / confusion: 71.62% / [[211, 140], [87, 362]], * Val accuracy / confusion: 69.62% / [[119, 111], [47, 243]] ------------------------------ Epoch 065 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.712503 - Iter 024 / 025, Loss: 0.477809 * Train accuracy / confusion: 71.25% / [[236, 121], [109, 334]], * Val accuracy / confusion: 71.73% / [[186, 44], [103, 187]] ------------------------------ Epoch 066 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.570940 - Iter 024 / 025, Loss: 0.480095 * Train accuracy / confusion: 71.75% / [[233, 123], [103, 341]], * Val accuracy / confusion: 73.85% / [[171, 59], [77, 213]] ------------------------------ Epoch 067 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.506600 - Iter 024 / 025, Loss: 0.586443 * Train accuracy / confusion: 68.88% / [[238, 117], [132, 313]], * Val accuracy / confusion: 71.54% / [[183, 47], [101, 189]] ------------------------------ Epoch 068 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.534427 - Iter 024 / 025, Loss: 0.652093 * Train accuracy / confusion: 71.50% / [[243, 114], [114, 329]], * Val accuracy / confusion: 70.19% / [[109, 121], [34, 256]] ------------------------------ Epoch 069 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.574924 - Iter 024 / 025, Loss: 0.524847 * Train accuracy / confusion: 71.62% / [[233, 123], [104, 340]], * Val accuracy / confusion: 70.00% / [[121, 109], [47, 243]] ------------------------------ Epoch 070 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.706084 - Iter 024 / 025, Loss: 0.494342 * Train accuracy / confusion: 70.62% / [[215, 142], [93, 350]], * Val accuracy / confusion: 73.46% / [[133, 97], [41, 249]] ------------------------------ Epoch 071 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.532548 - Iter 024 / 025, Loss: 0.627726 * Train accuracy / confusion: 72.12% / [[228, 124], [99, 349]], * Val accuracy / confusion: 73.27% / [[173, 57], [82, 208]] ------------------------------ Epoch 072 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.564893 - Iter 024 / 025, Loss: 0.499369 * Train accuracy / confusion: 71.62% / [[219, 138], [89, 354]], * Val accuracy / confusion: 73.85% / [[135, 95], [41, 249]] ------------------------------ Epoch 073 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.548896 - Iter 024 / 025, Loss: 0.513369 * Train accuracy / confusion: 73.00% / [[221, 137], [79, 363]], * Val accuracy / confusion: 73.85% / [[146, 84], [52, 238]] ------------------------------ Epoch 074 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.808513 - Iter 024 / 025, Loss: 0.529252 * Train accuracy / confusion: 71.88% / [[218, 142], [83, 357]], * Val accuracy / confusion: 73.27% / [[124, 106], [33, 257]] ------------------------------ Epoch 075 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.430703 - Iter 024 / 025, Loss: 0.671758 * Train accuracy / confusion: 73.50% / [[241, 114], [98, 347]], * Val accuracy / confusion: 71.35% / [[110, 120], [29, 261]] ------------------------------ Epoch 076 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.544997 - Iter 024 / 025, Loss: 0.528418 * Train accuracy / confusion: 72.38% / [[221, 136], [85, 358]], * Val accuracy / confusion: 72.12% / [[118, 112], [33, 257]] ------------------------------ Epoch 077 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.536551 - Iter 024 / 025, Loss: 0.529041 * Train accuracy / confusion: 72.00% / [[230, 128], [96, 346]], * Val accuracy / confusion: 67.12% / [[94, 136], [35, 255]] ------------------------------ Epoch 078 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.558918 - Iter 024 / 025, Loss: 0.714880 * Train accuracy / confusion: 74.50% / [[251, 106], [98, 345]], * Val accuracy / confusion: 74.62% / [[148, 82], [50, 240]] ------------------------------ Epoch 079 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.535818 - Iter 024 / 025, Loss: 0.601846 * Train accuracy / confusion: 74.12% / [[245, 108], [99, 348]], * Val accuracy / confusion: 70.77% / [[186, 44], [108, 182]] ------------------------------ Epoch 080 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.549668 - Iter 024 / 025, Loss: 0.651817 * Train accuracy / confusion: 73.62% / [[239, 121], [90, 350]], * Val accuracy / confusion: 73.08% / [[116, 114], [26, 264]] ------------------------------ Epoch 081 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.505583 - Iter 024 / 025, Loss: 0.595700 * Train accuracy / confusion: 70.88% / [[237, 119], [114, 330]], * Val accuracy / confusion: 75.00% / [[159, 71], [59, 231]] ------------------------------ Epoch 082 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390654 - Iter 024 / 025, Loss: 0.603804 * Train accuracy / confusion: 73.38% / [[227, 126], [87, 360]], * Val accuracy / confusion: 75.96% / [[170, 60], [65, 225]] ------------------------------ Epoch 083 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.412878 - Iter 024 / 025, Loss: 0.442693 * Train accuracy / confusion: 74.50% / [[226, 126], [78, 370]], * Val accuracy / confusion: 76.54% / [[154, 76], [46, 244]] ------------------------------ Epoch 084 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.441746 - Iter 024 / 025, Loss: 0.635894 * Train accuracy / confusion: 74.75% / [[239, 113], [89, 359]], * Val accuracy / confusion: 72.88% / [[122, 108], [33, 257]] ------------------------------ Epoch 085 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.643116 - Iter 024 / 025, Loss: 0.561897 * Train accuracy / confusion: 74.38% / [[261, 97], [108, 334]], * Val accuracy / confusion: 73.46% / [[147, 83], [55, 235]] ------------------------------ Epoch 086 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.577556 - Iter 024 / 025, Loss: 0.524663 * Train accuracy / confusion: 73.62% / [[227, 132], [79, 362]], * Val accuracy / confusion: 75.38% / [[160, 70], [58, 232]] ------------------------------ Epoch 087 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.490047 - Iter 024 / 025, Loss: 0.922822 * Train accuracy / confusion: 73.50% / [[246, 107], [105, 342]], * Val accuracy / confusion: 72.12% / [[133, 97], [48, 242]] ------------------------------ Epoch 088 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.599867 - Iter 024 / 025, Loss: 0.472153 * Train accuracy / confusion: 75.62% / [[246, 109], [86, 359]], * Val accuracy / confusion: 65.58% / [[68, 162], [17, 273]] ------------------------------ Epoch 089 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.537521 - Iter 024 / 025, Loss: 0.467458 * Train accuracy / confusion: 72.62% / [[223, 135], [84, 358]], * Val accuracy / confusion: 75.58% / [[139, 91], [36, 254]] ------------------------------ Epoch 090 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.509683 - Iter 024 / 025, Loss: 0.593771 * Train accuracy / confusion: 73.50% / [[237, 116], [96, 351]], * Val accuracy / confusion: 76.54% / [[156, 74], [48, 242]] ------------------------------ Epoch 091 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.528541 - Iter 024 / 025, Loss: 0.551550 * Train accuracy / confusion: 73.50% / [[247, 110], [102, 341]], * Val accuracy / confusion: 68.27% / [[88, 142], [23, 267]] ------------------------------ Epoch 092 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.541307 - Iter 024 / 025, Loss: 0.665859 * Train accuracy / confusion: 72.62% / [[225, 128], [91, 356]], * Val accuracy / confusion: 73.08% / [[142, 88], [52, 238]] ------------------------------ Epoch 093 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433731 - Iter 024 / 025, Loss: 0.685091 * Train accuracy / confusion: 72.88% / [[219, 138], [79, 364]], * Val accuracy / confusion: 74.04% / [[132, 98], [37, 253]] ------------------------------ Epoch 094 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547640 - Iter 024 / 025, Loss: 0.520632 * Train accuracy / confusion: 73.50% / [[253, 103], [109, 335]], * Val accuracy / confusion: 75.00% / [[160, 70], [60, 230]] ------------------------------ Epoch 095 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488512 - Iter 024 / 025, Loss: 0.656519 * Train accuracy / confusion: 74.12% / [[235, 122], [85, 358]], * Val accuracy / confusion: 74.62% / [[165, 65], [67, 223]] ------------------------------ Epoch 096 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.493540 - Iter 024 / 025, Loss: 0.440547 * Train accuracy / confusion: 73.00% / [[238, 122], [94, 346]], * Val accuracy / confusion: 72.31% / [[129, 101], [43, 247]] ------------------------------ Epoch 097 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.685417 - Iter 024 / 025, Loss: 0.616280 * Train accuracy / confusion: 73.12% / [[221, 133], [82, 364]], * Val accuracy / confusion: 71.15% / [[148, 82], [68, 222]] ------------------------------ Epoch 098 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.444131 - Iter 024 / 025, Loss: 0.604003 * Train accuracy / confusion: 73.88% / [[233, 124], [85, 358]], * Val accuracy / confusion: 73.27% / [[144, 86], [53, 237]] ------------------------------ Epoch 099 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.688064 - Iter 024 / 025, Loss: 0.632589 * Train accuracy / confusion: 72.12% / [[228, 131], [92, 349]], * Val accuracy / confusion: 68.65% / [[112, 118], [45, 245]] ------------------------------ Epoch 100 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517671 - Iter 024 / 025, Loss: 0.500082 * Train accuracy / confusion: 71.75% / [[230, 129], [97, 344]], * Val accuracy / confusion: 73.08% / [[142, 88], [52, 238]] ------------------------------ Epoch 101 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.522937 - Iter 024 / 025, Loss: 0.561661 * Train accuracy / confusion: 73.00% / [[229, 125], [91, 355]], * Val accuracy / confusion: 68.46% / [[99, 131], [33, 257]] ------------------------------ Epoch 102 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.589620 - Iter 024 / 025, Loss: 0.452670 * Train accuracy / confusion: 73.50% / [[228, 125], [87, 360]], * Val accuracy / confusion: 75.00% / [[144, 86], [44, 246]] ------------------------------ Epoch 103 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.654886 - Iter 024 / 025, Loss: 0.491417 * Train accuracy / confusion: 72.25% / [[242, 111], [111, 336]], * Val accuracy / confusion: 71.15% / [[125, 105], [45, 245]] ------------------------------ Epoch 104 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.424805 - Iter 024 / 025, Loss: 0.515546 * Train accuracy / confusion: 74.50% / [[225, 132], [72, 371]], * Val accuracy / confusion: 74.81% / [[136, 94], [37, 253]] ------------------------------ Epoch 105 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.424168 - Iter 024 / 025, Loss: 0.539966 * Train accuracy / confusion: 71.50% / [[210, 144], [84, 362]], * Val accuracy / confusion: 69.04% / [[97, 133], [28, 262]] ------------------------------ Epoch 106 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.693537 - Iter 024 / 025, Loss: 0.408476 * Train accuracy / confusion: 73.62% / [[232, 125], [86, 357]], * Val accuracy / confusion: 66.92% / [[86, 144], [28, 262]] ------------------------------ Epoch 107 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.376113 - Iter 024 / 025, Loss: 0.551685 * Train accuracy / confusion: 73.75% / [[232, 120], [90, 358]], * Val accuracy / confusion: 72.50% / [[129, 101], [42, 248]] ------------------------------ Epoch 108 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.511891 - Iter 024 / 025, Loss: 0.572073 * Train accuracy / confusion: 75.62% / [[240, 116], [79, 365]], * Val accuracy / confusion: 70.96% / [[134, 96], [55, 235]] ------------------------------ Epoch 109 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.561101 - Iter 024 / 025, Loss: 0.591117 * Train accuracy / confusion: 74.12% / [[234, 120], [87, 359]], * Val accuracy / confusion: 70.00% / [[108, 122], [34, 256]] ------------------------------ Epoch 110 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.671075 - Iter 024 / 025, Loss: 0.568420 * Train accuracy / confusion: 73.38% / [[243, 118], [95, 344]], * Val accuracy / confusion: 73.85% / [[133, 97], [39, 251]] ------------------------------ Epoch 111 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.510358 - Iter 024 / 025, Loss: 0.604928 * Train accuracy / confusion: 76.25% / [[243, 116], [74, 367]], * Val accuracy / confusion: 76.35% / [[160, 70], [53, 237]] ------------------------------ Epoch 112 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.394846 - Iter 024 / 025, Loss: 0.439316 * Train accuracy / confusion: 73.62% / [[257, 102], [109, 332]], * Val accuracy / confusion: 73.65% / [[147, 83], [54, 236]] ------------------------------ Epoch 113 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.527137 - Iter 024 / 025, Loss: 0.553025 * Train accuracy / confusion: 75.12% / [[254, 104], [95, 347]], * Val accuracy / confusion: 70.19% / [[113, 117], [38, 252]] ------------------------------ Epoch 114 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.314877 - Iter 024 / 025, Loss: 0.506058 * Train accuracy / confusion: 74.50% / [[236, 113], [91, 360]], * Val accuracy / confusion: 67.69% / [[106, 124], [44, 246]] ------------------------------ Epoch 115 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.572860 - Iter 024 / 025, Loss: 0.430226 * Train accuracy / confusion: 74.62% / [[227, 128], [75, 370]], * Val accuracy / confusion: 69.81% / [[101, 129], [28, 262]] ------------------------------ Epoch 116 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.396949 - Iter 024 / 025, Loss: 0.511421 * Train accuracy / confusion: 73.62% / [[245, 111], [100, 344]], * Val accuracy / confusion: 72.88% / [[123, 107], [34, 256]] ------------------------------ Epoch 117 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473068 - Iter 024 / 025, Loss: 0.626955 * Train accuracy / confusion: 76.75% / [[242, 113], [73, 372]], * Val accuracy / confusion: 72.50% / [[127, 103], [40, 250]] ------------------------------ Epoch 118 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.692602 - Iter 024 / 025, Loss: 0.585180 * Train accuracy / confusion: 73.00% / [[226, 129], [87, 358]], * Val accuracy / confusion: 70.00% / [[104, 126], [30, 260]] ------------------------------ Epoch 119 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.713018 - Iter 024 / 025, Loss: 0.490221 * Train accuracy / confusion: 76.00% / [[250, 107], [85, 358]], * Val accuracy / confusion: 72.12% / [[128, 102], [43, 247]] ------------------------------ Epoch 120 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.338291 - Iter 024 / 025, Loss: 0.532583 * Train accuracy / confusion: 75.50% / [[258, 103], [93, 346]], * Val accuracy / confusion: 71.92% / [[126, 104], [42, 248]] ------------------------------ Epoch 121 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.472371 - Iter 024 / 025, Loss: 0.505800 * Train accuracy / confusion: 73.88% / [[243, 116], [93, 348]], * Val accuracy / confusion: 64.42% / [[58, 172], [13, 277]] ------------------------------ Epoch 122 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517666 - Iter 024 / 025, Loss: 0.552411 * Train accuracy / confusion: 74.50% / [[242, 115], [89, 354]], * Val accuracy / confusion: 71.73% / [[170, 60], [87, 203]] ------------------------------ Epoch 123 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.427188 - Iter 024 / 025, Loss: 0.526556 * Train accuracy / confusion: 75.38% / [[241, 116], [81, 362]], * Val accuracy / confusion: 70.19% / [[103, 127], [28, 262]] ------------------------------ Epoch 124 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.624751 - Iter 024 / 025, Loss: 0.377695 * Train accuracy / confusion: 73.88% / [[237, 120], [89, 354]], * Val accuracy / confusion: 73.46% / [[145, 85], [53, 237]] ------------------------------ Epoch 125 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.622474 - Iter 024 / 025, Loss: 0.728108 * Train accuracy / confusion: 74.12% / [[235, 119], [88, 358]], * Val accuracy / confusion: 69.23% / [[102, 128], [32, 258]] ------------------------------ Epoch 126 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.485195 - Iter 024 / 025, Loss: 0.476828 * Train accuracy / confusion: 74.88% / [[245, 111], [90, 354]], * Val accuracy / confusion: 72.88% / [[138, 92], [49, 241]] ------------------------------ Epoch 127 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.463244 - Iter 024 / 025, Loss: 0.474422 * Train accuracy / confusion: 76.00% / [[253, 108], [84, 355]], * Val accuracy / confusion: 70.58% / [[119, 111], [42, 248]] ------------------------------ Epoch 128 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.375163 - Iter 024 / 025, Loss: 0.512591 * Train accuracy / confusion: 72.12% / [[234, 124], [99, 343]], * Val accuracy / confusion: 74.23% / [[170, 60], [74, 216]] ------------------------------ Epoch 129 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464410 - Iter 024 / 025, Loss: 0.510662 * Train accuracy / confusion: 73.50% / [[240, 118], [94, 348]], * Val accuracy / confusion: 66.54% / [[82, 148], [26, 264]] ------------------------------ Epoch 130 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.516037 - Iter 024 / 025, Loss: 0.380481 * Train accuracy / confusion: 75.25% / [[252, 105], [93, 350]], * Val accuracy / confusion: 74.04% / [[140, 90], [45, 245]] ------------------------------ Epoch 131 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.616000 - Iter 024 / 025, Loss: 0.480058 * Train accuracy / confusion: 74.00% / [[242, 113], [95, 350]], * Val accuracy / confusion: 77.50% / [[172, 58], [59, 231]] ------------------------------ Epoch 132 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.566425 - Iter 024 / 025, Loss: 0.655279 * Train accuracy / confusion: 72.62% / [[233, 122], [97, 348]], * Val accuracy / confusion: 69.81% / [[107, 123], [34, 256]] ------------------------------ Epoch 133 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.421661 - Iter 024 / 025, Loss: 0.394216 * Train accuracy / confusion: 75.75% / [[244, 111], [83, 362]], * Val accuracy / confusion: 70.00% / [[122, 108], [48, 242]] ------------------------------ Epoch 134 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.521655 - Iter 024 / 025, Loss: 0.405277 * Train accuracy / confusion: 74.62% / [[224, 128], [75, 373]], * Val accuracy / confusion: 71.73% / [[127, 103], [44, 246]] ------------------------------ Epoch 135 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.474340 - Iter 024 / 025, Loss: 0.763104 * Train accuracy / confusion: 75.12% / [[243, 111], [88, 358]], * Val accuracy / confusion: 70.77% / [[114, 116], [36, 254]] ------------------------------ Epoch 136 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.592936 - Iter 024 / 025, Loss: 0.581850 * Train accuracy / confusion: 76.38% / [[253, 109], [80, 358]], * Val accuracy / confusion: 72.31% / [[141, 89], [55, 235]] ------------------------------ Epoch 137 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.576953 - Iter 024 / 025, Loss: 0.578184 * Train accuracy / confusion: 75.00% / [[244, 108], [92, 356]], * Val accuracy / confusion: 69.23% / [[99, 131], [29, 261]] ------------------------------ Epoch 138 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.470353 - Iter 024 / 025, Loss: 0.707175 * Train accuracy / confusion: 74.00% / [[248, 108], [100, 344]], * Val accuracy / confusion: 73.65% / [[138, 92], [45, 245]] ------------------------------ Epoch 139 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.387736 - Iter 024 / 025, Loss: 0.565383 * Train accuracy / confusion: 74.75% / [[244, 115], [87, 354]], * Val accuracy / confusion: 76.92% / [[151, 79], [41, 249]] ------------------------------ Epoch 140 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.426969 - Iter 024 / 025, Loss: 0.381867 * Train accuracy / confusion: 74.88% / [[246, 115], [86, 353]], * Val accuracy / confusion: 75.58% / [[147, 83], [44, 246]] ------------------------------ Epoch 141 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.730789 - Iter 024 / 025, Loss: 0.432964 * Train accuracy / confusion: 74.75% / [[259, 101], [101, 339]], * Val accuracy / confusion: 74.04% / [[167, 63], [72, 218]] ------------------------------ Epoch 142 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433728 - Iter 024 / 025, Loss: 0.522781 * Train accuracy / confusion: 74.75% / [[247, 108], [94, 351]], * Val accuracy / confusion: 74.23% / [[169, 61], [73, 217]] ------------------------------ Epoch 143 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.537194 - Iter 024 / 025, Loss: 0.539292 * Train accuracy / confusion: 73.25% / [[235, 120], [94, 351]], * Val accuracy / confusion: 69.42% / [[99, 131], [28, 262]] ------------------------------ Epoch 144 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.558577 - Iter 024 / 025, Loss: 0.525237 * Train accuracy / confusion: 74.00% / [[239, 119], [89, 353]], * Val accuracy / confusion: 72.69% / [[138, 92], [50, 240]] ------------------------------ Epoch 145 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.485350 - Iter 024 / 025, Loss: 0.636815 * Train accuracy / confusion: 75.25% / [[245, 105], [93, 357]], * Val accuracy / confusion: 71.15% / [[147, 83], [67, 223]] ------------------------------ Epoch 146 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.402517 - Iter 024 / 025, Loss: 0.531896 * Train accuracy / confusion: 75.00% / [[238, 118], [82, 362]], * Val accuracy / confusion: 73.85% / [[135, 95], [41, 249]] ------------------------------ Epoch 147 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.529368 - Iter 024 / 025, Loss: 0.631726 * Train accuracy / confusion: 74.12% / [[251, 106], [101, 342]], * Val accuracy / confusion: 73.08% / [[134, 96], [44, 246]] ------------------------------ Epoch 148 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.516262 - Iter 024 / 025, Loss: 0.474633 * Train accuracy / confusion: 75.25% / [[248, 108], [90, 354]], * Val accuracy / confusion: 75.58% / [[155, 75], [52, 238]] ------------------------------ Epoch 149 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.389749 - Iter 024 / 025, Loss: 0.717357 * Train accuracy / confusion: 75.62% / [[252, 99], [96, 353]], * Val accuracy / confusion: 74.81% / [[153, 77], [54, 236]] ------------------------------ Epoch 150 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.375310 - Iter 024 / 025, Loss: 0.566860 * Train accuracy / confusion: 76.75% / [[248, 107], [79, 366]], * Val accuracy / confusion: 73.85% / [[138, 92], [44, 246]] ------------------------------ Epoch 151 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.379689 - Iter 024 / 025, Loss: 0.502485 * Train accuracy / confusion: 76.50% / [[264, 92], [96, 348]], * Val accuracy / confusion: 71.54% / [[118, 112], [36, 254]] ------------------------------ Epoch 152 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519084 - Iter 024 / 025, Loss: 0.434575 * Train accuracy / confusion: 75.88% / [[243, 108], [85, 364]], * Val accuracy / confusion: 71.92% / [[134, 96], [50, 240]] ------------------------------ Epoch 153 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.349604 - Iter 024 / 025, Loss: 0.407178 * Train accuracy / confusion: 76.62% / [[255, 98], [89, 358]], * Val accuracy / confusion: 71.92% / [[121, 109], [37, 253]] ------------------------------ Epoch 154 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.460614 - Iter 024 / 025, Loss: 0.631160 * Train accuracy / confusion: 75.50% / [[247, 111], [85, 357]], * Val accuracy / confusion: 71.54% / [[142, 88], [60, 230]] ------------------------------ Epoch 155 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.597304 - Iter 024 / 025, Loss: 0.572714 * Train accuracy / confusion: 74.12% / [[236, 119], [88, 357]], * Val accuracy / confusion: 72.88% / [[132, 98], [43, 247]] ------------------------------ Epoch 156 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477020 - Iter 024 / 025, Loss: 0.448592 * Train accuracy / confusion: 75.88% / [[241, 114], [79, 366]], * Val accuracy / confusion: 75.58% / [[150, 80], [47, 243]] ------------------------------ Epoch 157 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.468605 - Iter 024 / 025, Loss: 0.454774 * Train accuracy / confusion: 76.50% / [[251, 99], [89, 361]], * Val accuracy / confusion: 74.23% / [[145, 85], [49, 241]] ------------------------------ Epoch 158 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.561962 - Iter 024 / 025, Loss: 0.402327 * Train accuracy / confusion: 77.00% / [[261, 95], [89, 355]], * Val accuracy / confusion: 76.35% / [[149, 81], [42, 248]] ------------------------------ Epoch 159 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.340766 - Iter 024 / 025, Loss: 0.376907 * Train accuracy / confusion: 77.25% / [[258, 96], [86, 360]], * Val accuracy / confusion: 71.35% / [[119, 111], [38, 252]] ------------------------------ Epoch 160 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473111 - Iter 024 / 025, Loss: 0.683784 * Train accuracy / confusion: 75.62% / [[238, 119], [76, 367]], * Val accuracy / confusion: 73.85% / [[138, 92], [44, 246]] ------------------------------ Epoch 161 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591780 - Iter 024 / 025, Loss: 0.422377 * Train accuracy / confusion: 76.50% / [[258, 98], [90, 354]], * Val accuracy / confusion: 75.19% / [[183, 47], [82, 208]] ------------------------------ Epoch 162 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.390372 - Iter 024 / 025, Loss: 0.678774 * Train accuracy / confusion: 76.00% / [[246, 108], [84, 362]], * Val accuracy / confusion: 72.31% / [[152, 78], [66, 224]] ------------------------------ Epoch 163 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.443536 - Iter 024 / 025, Loss: 0.719208 * Train accuracy / confusion: 77.75% / [[255, 98], [80, 367]], * Val accuracy / confusion: 70.00% / [[114, 116], [40, 250]] ------------------------------ Epoch 164 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.498793 - Iter 024 / 025, Loss: 0.571632 * Train accuracy / confusion: 76.50% / [[258, 98], [90, 354]], * Val accuracy / confusion: 72.31% / [[152, 78], [66, 224]] ------------------------------ Epoch 165 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.685022 - Iter 024 / 025, Loss: 0.640822 * Train accuracy / confusion: 75.75% / [[247, 114], [80, 359]], * Val accuracy / confusion: 69.23% / [[85, 145], [15, 275]] ------------------------------ Epoch 166 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.511172 - Iter 024 / 025, Loss: 0.377317 * Train accuracy / confusion: 75.62% / [[257, 99], [96, 348]], * Val accuracy / confusion: 75.19% / [[161, 69], [60, 230]] ------------------------------ Epoch 167 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.499952 - Iter 024 / 025, Loss: 0.490134 * Train accuracy / confusion: 75.88% / [[254, 102], [91, 353]], * Val accuracy / confusion: 70.00% / [[106, 124], [32, 258]] ------------------------------ Epoch 168 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.450146 - Iter 024 / 025, Loss: 0.493525 * Train accuracy / confusion: 75.12% / [[249, 106], [93, 352]], * Val accuracy / confusion: 71.92% / [[127, 103], [43, 247]] ------------------------------ Epoch 169 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.549995 - Iter 024 / 025, Loss: 0.676324 * Train accuracy / confusion: 75.62% / [[249, 108], [87, 356]], * Val accuracy / confusion: 72.50% / [[133, 97], [46, 244]] ------------------------------ Epoch 170 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.417242 - Iter 024 / 025, Loss: 0.657853 * Train accuracy / confusion: 77.12% / [[254, 103], [80, 363]], * Val accuracy / confusion: 70.38% / [[116, 114], [40, 250]] ------------------------------ Epoch 171 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.528678 - Iter 024 / 025, Loss: 0.442921 * Train accuracy / confusion: 73.75% / [[250, 109], [101, 340]], * Val accuracy / confusion: 71.92% / [[169, 61], [85, 205]] ------------------------------ Epoch 172 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.465282 - Iter 024 / 025, Loss: 0.508458 * Train accuracy / confusion: 75.25% / [[235, 117], [81, 367]], * Val accuracy / confusion: 72.12% / [[148, 82], [63, 227]] ------------------------------ Epoch 173 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.512443 - Iter 024 / 025, Loss: 0.658445 * Train accuracy / confusion: 75.00% / [[239, 114], [86, 361]], * Val accuracy / confusion: 72.31% / [[128, 102], [42, 248]] ------------------------------ Epoch 174 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.464481 - Iter 024 / 025, Loss: 0.456863 * Train accuracy / confusion: 77.00% / [[253, 98], [86, 363]], * Val accuracy / confusion: 72.31% / [[135, 95], [49, 241]] ------------------------------ Epoch 175 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.558878 - Iter 024 / 025, Loss: 0.492723 * Train accuracy / confusion: 74.75% / [[245, 113], [89, 353]], * Val accuracy / confusion: 71.35% / [[142, 88], [61, 229]] ------------------------------ Epoch 176 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.371431 - Iter 024 / 025, Loss: 0.547690 * Train accuracy / confusion: 75.62% / [[247, 106], [89, 358]], * Val accuracy / confusion: 68.46% / [[108, 122], [42, 248]] ------------------------------ Epoch 177 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.538965 - Iter 024 / 025, Loss: 0.552779 * Train accuracy / confusion: 75.12% / [[237, 121], [78, 364]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] ------------------------------ Epoch 178 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.481598 - Iter 024 / 025, Loss: 0.648581 * Train accuracy / confusion: 76.62% / [[259, 98], [89, 354]], * Val accuracy / confusion: 73.08% / [[131, 99], [41, 249]] ------------------------------ Epoch 179 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.444536 - Iter 024 / 025, Loss: 0.510141 * Train accuracy / confusion: 76.88% / [[256, 101], [84, 359]], * Val accuracy / confusion: 72.31% / [[116, 114], [30, 260]] ------------------------------ Epoch 180 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.728937 - Iter 024 / 025, Loss: 0.645512 * Train accuracy / confusion: 74.75% / [[250, 107], [95, 348]], * Val accuracy / confusion: 70.96% / [[110, 120], [31, 259]] ------------------------------ Epoch 181 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519232 - Iter 024 / 025, Loss: 0.584205 * Train accuracy / confusion: 75.38% / [[252, 105], [92, 351]], * Val accuracy / confusion: 72.31% / [[147, 83], [61, 229]] ------------------------------ Epoch 182 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.553318 - Iter 024 / 025, Loss: 0.432806 * Train accuracy / confusion: 75.00% / [[240, 117], [83, 360]], * Val accuracy / confusion: 67.50% / [[101, 129], [40, 250]] ------------------------------ Epoch 183 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.437602 - Iter 024 / 025, Loss: 0.503694 * Train accuracy / confusion: 75.88% / [[249, 108], [85, 358]], * Val accuracy / confusion: 67.31% / [[90, 140], [30, 260]] ------------------------------ Epoch 184 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.549772 - Iter 024 / 025, Loss: 0.526471 * Train accuracy / confusion: 77.50% / [[258, 99], [81, 362]], * Val accuracy / confusion: 71.15% / [[147, 83], [67, 223]] ------------------------------ Epoch 185 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.457207 - Iter 024 / 025, Loss: 0.321425 * Train accuracy / confusion: 75.50% / [[239, 118], [78, 365]], * Val accuracy / confusion: 71.54% / [[129, 101], [47, 243]] ------------------------------ Epoch 186 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.402882 - Iter 024 / 025, Loss: 0.597551 * Train accuracy / confusion: 76.25% / [[245, 110], [80, 365]], * Val accuracy / confusion: 68.27% / [[90, 140], [25, 265]] ------------------------------ Epoch 187 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.532412 - Iter 024 / 025, Loss: 0.546034 * Train accuracy / confusion: 75.75% / [[241, 114], [80, 365]], * Val accuracy / confusion: 70.58% / [[126, 104], [49, 241]] ------------------------------ Epoch 188 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.590972 - Iter 024 / 025, Loss: 0.415156 * Train accuracy / confusion: 76.50% / [[252, 102], [86, 360]], * Val accuracy / confusion: 71.54% / [[130, 100], [48, 242]] ------------------------------ Epoch 189 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.511661 - Iter 024 / 025, Loss: 0.582675 * Train accuracy / confusion: 76.50% / [[247, 109], [79, 365]], * Val accuracy / confusion: 70.58% / [[178, 52], [101, 189]] ------------------------------ Epoch 190 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.351460 - Iter 024 / 025, Loss: 0.421908 * Train accuracy / confusion: 75.62% / [[243, 112], [83, 362]], * Val accuracy / confusion: 66.92% / [[92, 138], [34, 256]] ------------------------------ Epoch 191 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.496317 - Iter 024 / 025, Loss: 0.606759 * Train accuracy / confusion: 77.00% / [[245, 113], [71, 371]], * Val accuracy / confusion: 72.50% / [[159, 71], [72, 218]] ------------------------------ Epoch 192 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.633411 - Iter 024 / 025, Loss: 0.621650 * Train accuracy / confusion: 74.88% / [[238, 117], [84, 361]], * Val accuracy / confusion: 73.27% / [[155, 75], [64, 226]] ------------------------------ Epoch 193 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.531975 - Iter 024 / 025, Loss: 0.596418 * Train accuracy / confusion: 76.50% / [[242, 112], [76, 370]], * Val accuracy / confusion: 72.88% / [[161, 69], [72, 218]] ------------------------------ Epoch 194 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.395040 - Iter 024 / 025, Loss: 0.598165 * Train accuracy / confusion: 74.25% / [[242, 119], [87, 352]], * Val accuracy / confusion: 68.85% / [[101, 129], [33, 257]] ------------------------------ Epoch 195 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483556 - Iter 024 / 025, Loss: 0.545124 * Train accuracy / confusion: 75.62% / [[248, 106], [89, 357]], * Val accuracy / confusion: 71.73% / [[132, 98], [49, 241]] ------------------------------ Epoch 196 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.437988 - Iter 024 / 025, Loss: 0.507122 * Train accuracy / confusion: 75.75% / [[246, 108], [86, 360]], * Val accuracy / confusion: 70.96% / [[136, 94], [57, 233]] ------------------------------ Epoch 197 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.613353 - Iter 024 / 025, Loss: 0.325183 * Train accuracy / confusion: 78.50% / [[250, 107], [65, 378]], * Val accuracy / confusion: 71.15% / [[136, 94], [56, 234]] ------------------------------ Epoch 198 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.412903 - Iter 024 / 025, Loss: 0.497397 * Train accuracy / confusion: 77.88% / [[251, 100], [77, 372]], * Val accuracy / confusion: 73.46% / [[140, 90], [48, 242]] ------------------------------ Epoch 199 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.539594 - Iter 024 / 025, Loss: 0.492380 * Train accuracy / confusion: 77.50% / [[251, 107], [73, 369]], * Val accuracy / confusion: 69.04% / [[118, 112], [49, 241]] ------------------------------ Epoch 200 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.487508 - Iter 024 / 025, Loss: 0.413943 * Train accuracy / confusion: 76.88% / [[263, 92], [93, 352]], * Val accuracy / confusion: 74.81% / [[152, 78], [53, 237]] ------------------------------ Epoch 201 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.422182 - Iter 024 / 025, Loss: 0.455175 * Train accuracy / confusion: 77.75% / [[263, 100], [78, 359]], * Val accuracy / confusion: 71.73% / [[127, 103], [44, 246]] ------------------------------ Epoch 202 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.536840 - Iter 024 / 025, Loss: 0.465109 * Train accuracy / confusion: 76.62% / [[259, 97], [90, 354]], * Val accuracy / confusion: 71.73% / [[133, 97], [50, 240]] ------------------------------ Epoch 203 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.375573 - Iter 024 / 025, Loss: 0.618533 * Train accuracy / confusion: 76.00% / [[249, 105], [87, 359]], * Val accuracy / confusion: 70.19% / [[131, 99], [56, 234]] ------------------------------ Epoch 204 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.671078 - Iter 024 / 025, Loss: 0.374264 * Train accuracy / confusion: 75.75% / [[254, 101], [93, 352]], * Val accuracy / confusion: 72.69% / [[135, 95], [47, 243]] ------------------------------ Epoch 205 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.352937 - Iter 024 / 025, Loss: 0.362669 * Train accuracy / confusion: 75.75% / [[249, 104], [90, 357]], * Val accuracy / confusion: 73.85% / [[141, 89], [47, 243]] ------------------------------ Epoch 206 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.405923 - Iter 024 / 025, Loss: 0.670092 * Train accuracy / confusion: 77.25% / [[253, 100], [82, 365]], * Val accuracy / confusion: 71.54% / [[126, 104], [44, 246]] ------------------------------ Epoch 207 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.367101 - Iter 024 / 025, Loss: 0.417005 * Train accuracy / confusion: 75.88% / [[252, 107], [86, 355]], * Val accuracy / confusion: 74.04% / [[137, 93], [42, 248]] ------------------------------ Epoch 208 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.521386 - Iter 024 / 025, Loss: 0.549634 * Train accuracy / confusion: 77.75% / [[254, 106], [72, 368]], * Val accuracy / confusion: 71.35% / [[128, 102], [47, 243]] ------------------------------ Epoch 209 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.444514 - Iter 024 / 025, Loss: 0.332202 * Train accuracy / confusion: 78.12% / [[262, 94], [81, 363]], * Val accuracy / confusion: 74.81% / [[152, 78], [53, 237]] ------------------------------ Epoch 210 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.488439 - Iter 024 / 025, Loss: 0.413528 * Train accuracy / confusion: 77.25% / [[260, 96], [86, 358]], * Val accuracy / confusion: 72.50% / [[148, 82], [61, 229]] ------------------------------ Epoch 211 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.427083 - Iter 024 / 025, Loss: 0.523867 * Train accuracy / confusion: 77.00% / [[260, 95], [89, 356]], * Val accuracy / confusion: 71.54% / [[130, 100], [48, 242]] ------------------------------ Epoch 212 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.579909 - Iter 024 / 025, Loss: 0.598501 * Train accuracy / confusion: 80.88% / [[276, 84], [69, 371]], * Val accuracy / confusion: 70.58% / [[123, 107], [46, 244]] ------------------------------ Epoch 213 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.672326 - Iter 024 / 025, Loss: 0.500733 * Train accuracy / confusion: 75.12% / [[255, 109], [90, 346]], * Val accuracy / confusion: 69.81% / [[128, 102], [55, 235]] ------------------------------ Epoch 214 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.660851 - Iter 024 / 025, Loss: 0.355590 * Train accuracy / confusion: 77.75% / [[263, 96], [82, 359]], * Val accuracy / confusion: 73.85% / [[151, 79], [57, 233]] ------------------------------ Epoch 215 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.664071 - Iter 024 / 025, Loss: 0.430251 * Train accuracy / confusion: 77.25% / [[258, 99], [83, 360]], * Val accuracy / confusion: 72.88% / [[148, 82], [59, 231]] ------------------------------ Epoch 216 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.662528 - Iter 024 / 025, Loss: 0.490994 * Train accuracy / confusion: 77.12% / [[267, 90], [93, 350]], * Val accuracy / confusion: 71.92% / [[136, 94], [52, 238]] ------------------------------ Epoch 217 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.442049 - Iter 024 / 025, Loss: 0.599040 * Train accuracy / confusion: 77.00% / [[251, 101], [83, 365]], * Val accuracy / confusion: 71.92% / [[135, 95], [51, 239]] ------------------------------ Epoch 218 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.441235 - Iter 024 / 025, Loss: 0.922509 * Train accuracy / confusion: 76.75% / [[253, 105], [81, 361]], * Val accuracy / confusion: 73.65% / [[141, 89], [48, 242]] ------------------------------ Epoch 219 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.551341 - Iter 024 / 025, Loss: 0.458569 * Train accuracy / confusion: 77.12% / [[258, 96], [87, 359]], * Val accuracy / confusion: 71.54% / [[141, 89], [59, 231]] ------------------------------ Epoch 220 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.532909 - Iter 024 / 025, Loss: 0.675670 * Train accuracy / confusion: 76.62% / [[251, 103], [84, 362]], * Val accuracy / confusion: 69.81% / [[124, 106], [51, 239]] ------------------------------ Epoch 221 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.609129 - Iter 024 / 025, Loss: 0.534270 * Train accuracy / confusion: 74.88% / [[242, 111], [90, 357]], * Val accuracy / confusion: 70.00% / [[122, 108], [48, 242]] ------------------------------ Epoch 222 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.382171 - Iter 024 / 025, Loss: 0.513476 * Train accuracy / confusion: 78.12% / [[258, 97], [78, 367]], * Val accuracy / confusion: 73.08% / [[142, 88], [52, 238]] ------------------------------ Epoch 223 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.597935 - Iter 024 / 025, Loss: 0.404934 * Train accuracy / confusion: 78.00% / [[259, 96], [80, 365]], * Val accuracy / confusion: 72.50% / [[138, 92], [51, 239]] ------------------------------ Epoch 224 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.625530 - Iter 024 / 025, Loss: 0.567078 * Train accuracy / confusion: 78.62% / [[259, 94], [77, 370]], * Val accuracy / confusion: 70.38% / [[125, 105], [49, 241]] ------------------------------ Epoch 225 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.422379 - Iter 024 / 025, Loss: 0.500279 * Train accuracy / confusion: 74.62% / [[250, 109], [94, 347]], * Val accuracy / confusion: 70.96% / [[126, 104], [47, 243]] ------------------------------ Epoch 226 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.344627 - Iter 024 / 025, Loss: 0.488834 * Train accuracy / confusion: 77.75% / [[252, 104], [74, 370]], * Val accuracy / confusion: 70.58% / [[124, 106], [47, 243]] ------------------------------ Epoch 227 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.628277 - Iter 024 / 025, Loss: 0.667234 * Train accuracy / confusion: 77.62% / [[259, 98], [81, 362]], * Val accuracy / confusion: 71.92% / [[132, 98], [48, 242]] ------------------------------ Epoch 228 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.402189 - Iter 024 / 025, Loss: 0.434629 * Train accuracy / confusion: 79.88% / [[274, 85], [76, 365]], * Val accuracy / confusion: 70.96% / [[133, 97], [54, 236]] ------------------------------ Epoch 229 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.564596 - Iter 024 / 025, Loss: 0.534473 * Train accuracy / confusion: 76.25% / [[250, 102], [88, 360]], * Val accuracy / confusion: 74.62% / [[150, 80], [52, 238]] ------------------------------ Epoch 230 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.454572 - Iter 024 / 025, Loss: 0.430775 * Train accuracy / confusion: 77.50% / [[255, 101], [79, 365]], * Val accuracy / confusion: 68.65% / [[129, 101], [62, 228]] ------------------------------ Epoch 231 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.534464 - Iter 024 / 025, Loss: 0.407444 * Train accuracy / confusion: 77.88% / [[263, 98], [79, 360]], * Val accuracy / confusion: 71.73% / [[132, 98], [49, 241]] ------------------------------ Epoch 232 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.430521 - Iter 024 / 025, Loss: 0.381670 * Train accuracy / confusion: 77.00% / [[249, 104], [80, 367]], * Val accuracy / confusion: 70.38% / [[133, 97], [57, 233]] ------------------------------ Epoch 233 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.518710 - Iter 024 / 025, Loss: 0.601477 * Train accuracy / confusion: 77.38% / [[249, 111], [70, 370]], * Val accuracy / confusion: 72.12% / [[130, 100], [45, 245]] ------------------------------ Epoch 234 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.537215 - Iter 024 / 025, Loss: 0.423553 * Train accuracy / confusion: 79.38% / [[260, 95], [70, 375]], * Val accuracy / confusion: 70.00% / [[135, 95], [61, 229]] ------------------------------ Epoch 235 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.318835 - Iter 024 / 025, Loss: 0.446457 * Train accuracy / confusion: 77.00% / [[252, 106], [78, 364]], * Val accuracy / confusion: 68.46% / [[117, 113], [51, 239]] ------------------------------ Epoch 236 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.417508 - Iter 024 / 025, Loss: 0.615897 * Train accuracy / confusion: 77.62% / [[253, 101], [78, 368]], * Val accuracy / confusion: 71.73% / [[131, 99], [48, 242]] ------------------------------ Epoch 237 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.331252 - Iter 024 / 025, Loss: 0.375241 * Train accuracy / confusion: 77.62% / [[260, 98], [81, 361]], * Val accuracy / confusion: 73.08% / [[142, 88], [52, 238]] ------------------------------ Epoch 238 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.563050 - Iter 024 / 025, Loss: 0.570278 * Train accuracy / confusion: 78.12% / [[258, 99], [76, 367]], * Val accuracy / confusion: 71.92% / [[129, 101], [45, 245]] ------------------------------ Epoch 239 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.638357 - Iter 024 / 025, Loss: 0.435786 * Train accuracy / confusion: 78.50% / [[253, 105], [67, 375]], * Val accuracy / confusion: 70.58% / [[128, 102], [51, 239]] ------------------------------ Epoch 240 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.427303 - Iter 024 / 025, Loss: 0.458005 * Train accuracy / confusion: 76.88% / [[254, 104], [81, 361]], * Val accuracy / confusion: 71.54% / [[133, 97], [51, 239]] ------------------------------ Epoch 241 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.453329 - Iter 024 / 025, Loss: 0.369556 * Train accuracy / confusion: 77.25% / [[259, 95], [87, 359]], * Val accuracy / confusion: 68.46% / [[117, 113], [51, 239]] ------------------------------ Epoch 242 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.434804 - Iter 024 / 025, Loss: 0.472281 * Train accuracy / confusion: 77.50% / [[252, 103], [77, 368]], * Val accuracy / confusion: 70.77% / [[123, 107], [45, 245]] ------------------------------ Epoch 243 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.418802 - Iter 024 / 025, Loss: 0.393631 * Train accuracy / confusion: 80.38% / [[265, 94], [63, 378]], * Val accuracy / confusion: 70.77% / [[130, 100], [52, 238]] ------------------------------ Epoch 244 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.430868 - Iter 024 / 025, Loss: 0.656195 * Train accuracy / confusion: 78.25% / [[257, 102], [72, 369]], * Val accuracy / confusion: 69.42% / [[121, 109], [50, 240]] ------------------------------ Epoch 245 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.526386 - Iter 024 / 025, Loss: 0.438279 * Train accuracy / confusion: 77.00% / [[256, 101], [83, 360]], * Val accuracy / confusion: 69.81% / [[123, 107], [50, 240]] ------------------------------ Epoch 246 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.574319 - Iter 024 / 025, Loss: 0.587965 * Train accuracy / confusion: 77.62% / [[253, 106], [73, 368]], * Val accuracy / confusion: 72.50% / [[141, 89], [54, 236]] ------------------------------ Epoch 247 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.482492 - Iter 024 / 025, Loss: 0.458270 * Train accuracy / confusion: 78.62% / [[255, 98], [73, 374]], * Val accuracy / confusion: 68.46% / [[118, 112], [52, 238]] ------------------------------ Epoch 248 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.496534 - Iter 024 / 025, Loss: 0.439629 * Train accuracy / confusion: 76.88% / [[252, 107], [78, 363]], * Val accuracy / confusion: 71.54% / [[123, 107], [41, 249]] ------------------------------ Epoch 249 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.518610 - Iter 024 / 025, Loss: 0.635138 * Train accuracy / confusion: 77.25% / [[251, 105], [77, 367]], * Val accuracy / confusion: 72.88% / [[131, 99], [42, 248]] ------------------------------ Epoch 250 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.470705 - Iter 024 / 025, Loss: 0.650381 * Train accuracy / confusion: 77.25% / [[260, 99], [83, 358]], * Val accuracy / confusion: 71.73% / [[130, 100], [47, 243]] ------------------------------ Epoch 251 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.526153 - Iter 024 / 025, Loss: 0.607782 * Train accuracy / confusion: 77.88% / [[260, 100], [77, 363]], * Val accuracy / confusion: 72.12% / [[137, 93], [52, 238]] ------------------------------ Epoch 252 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.356654 - Iter 024 / 025, Loss: 0.519366 * Train accuracy / confusion: 79.12% / [[262, 91], [76, 371]], * Val accuracy / confusion: 71.15% / [[133, 97], [53, 237]] ------------------------------ Epoch 253 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.474865 - Iter 024 / 025, Loss: 0.587571 * Train accuracy / confusion: 78.75% / [[257, 93], [77, 373]], * Val accuracy / confusion: 74.04% / [[147, 83], [52, 238]] ------------------------------ Epoch 254 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.440841 - Iter 024 / 025, Loss: 0.672284 * Train accuracy / confusion: 77.88% / [[255, 100], [77, 368]], * Val accuracy / confusion: 72.69% / [[142, 88], [54, 236]] ------------------------------ Epoch 255 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.596733 - Iter 024 / 025, Loss: 0.637907 * Train accuracy / confusion: 79.25% / [[269, 91], [75, 365]], * Val accuracy / confusion: 73.46% / [[144, 86], [52, 238]] ------------------------------ Epoch 256 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.362569 - Iter 024 / 025, Loss: 0.513297 * Train accuracy / confusion: 77.50% / [[263, 97], [83, 357]], * Val accuracy / confusion: 72.12% / [[137, 93], [52, 238]] ------------------------------ Epoch 257 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.560781 - Iter 024 / 025, Loss: 0.329336 * Train accuracy / confusion: 78.12% / [[259, 99], [76, 366]], * Val accuracy / confusion: 71.15% / [[134, 96], [54, 236]] ------------------------------ Epoch 258 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.545702 - Iter 024 / 025, Loss: 0.504870 * Train accuracy / confusion: 79.38% / [[267, 86], [79, 368]], * Val accuracy / confusion: 71.92% / [[134, 96], [50, 240]] ------------------------------ Epoch 259 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.398333 - Iter 024 / 025, Loss: 0.447476 * Train accuracy / confusion: 77.25% / [[262, 94], [88, 356]], * Val accuracy / confusion: 73.65% / [[149, 81], [56, 234]] ------------------------------ Epoch 260 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.570328 - Iter 024 / 025, Loss: 0.534030 * Train accuracy / confusion: 75.12% / [[250, 109], [90, 351]], * Val accuracy / confusion: 74.04% / [[138, 92], [43, 247]] ------------------------------ Epoch 261 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.566554 - Iter 024 / 025, Loss: 0.402957 * Train accuracy / confusion: 78.12% / [[253, 99], [76, 372]], * Val accuracy / confusion: 72.31% / [[139, 91], [53, 237]] ------------------------------ Epoch 262 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466866 - Iter 024 / 025, Loss: 0.469360 * Train accuracy / confusion: 78.38% / [[261, 94], [79, 366]], * Val accuracy / confusion: 72.88% / [[134, 96], [45, 245]] ------------------------------ Epoch 263 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.447358 - Iter 024 / 025, Loss: 0.580530 * Train accuracy / confusion: 79.25% / [[266, 84], [82, 368]], * Val accuracy / confusion: 70.19% / [[130, 100], [55, 235]] ------------------------------ Epoch 264 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.520515 - Iter 024 / 025, Loss: 0.520314 * Train accuracy / confusion: 77.00% / [[255, 101], [83, 361]], * Val accuracy / confusion: 73.08% / [[131, 99], [41, 249]] ------------------------------ Epoch 265 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.599438 - Iter 024 / 025, Loss: 0.393711 * Train accuracy / confusion: 79.50% / [[271, 84], [80, 365]], * Val accuracy / confusion: 70.77% / [[134, 96], [56, 234]] ------------------------------ Epoch 266 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.596337 - Iter 024 / 025, Loss: 0.499017 * Train accuracy / confusion: 78.00% / [[256, 100], [76, 368]], * Val accuracy / confusion: 72.69% / [[141, 89], [53, 237]] ------------------------------ Epoch 267 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.474440 - Iter 024 / 025, Loss: 0.377802 * Train accuracy / confusion: 78.75% / [[259, 98], [72, 371]], * Val accuracy / confusion: 69.62% / [[121, 109], [49, 241]] ------------------------------ Epoch 268 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.586330 - Iter 024 / 025, Loss: 0.410539 * Train accuracy / confusion: 77.62% / [[262, 94], [85, 359]], * Val accuracy / confusion: 73.08% / [[138, 92], [48, 242]] ------------------------------ Epoch 269 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.411917 - Iter 024 / 025, Loss: 0.475037 * Train accuracy / confusion: 76.62% / [[250, 106], [81, 363]], * Val accuracy / confusion: 74.23% / [[144, 86], [48, 242]] ------------------------------ Epoch 270 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.441395 - Iter 024 / 025, Loss: 0.625452 * Train accuracy / confusion: 77.50% / [[262, 89], [91, 358]], * Val accuracy / confusion: 68.85% / [[132, 98], [64, 226]] ------------------------------ Epoch 271 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.520938 - Iter 024 / 025, Loss: 0.454057 * Train accuracy / confusion: 78.25% / [[267, 90], [84, 359]], * Val accuracy / confusion: 71.15% / [[130, 100], [50, 240]] ------------------------------ Epoch 272 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.278085 - Iter 024 / 025, Loss: 0.430865 * Train accuracy / confusion: 79.25% / [[270, 89], [77, 364]], * Val accuracy / confusion: 70.96% / [[129, 101], [50, 240]] ------------------------------ Epoch 273 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.399610 - Iter 024 / 025, Loss: 0.403951 * Train accuracy / confusion: 79.12% / [[254, 100], [67, 379]], * Val accuracy / confusion: 70.96% / [[134, 96], [55, 235]] ------------------------------ Epoch 274 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.420004 - Iter 024 / 025, Loss: 0.614238 * Train accuracy / confusion: 79.12% / [[250, 105], [62, 383]], * Val accuracy / confusion: 71.35% / [[133, 97], [52, 238]] ------------------------------ Epoch 275 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.511346 - Iter 024 / 025, Loss: 0.539948 * Train accuracy / confusion: 79.12% / [[262, 97], [70, 371]], * Val accuracy / confusion: 72.12% / [[135, 95], [50, 240]] ------------------------------ Epoch 276 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.583341 - Iter 024 / 025, Loss: 0.320760 * Train accuracy / confusion: 78.62% / [[257, 96], [75, 372]], * Val accuracy / confusion: 69.81% / [[133, 97], [60, 230]] ------------------------------ Epoch 277 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.447456 - Iter 024 / 025, Loss: 0.425356 * Train accuracy / confusion: 78.50% / [[258, 96], [76, 370]], * Val accuracy / confusion: 70.96% / [[123, 107], [44, 246]] ------------------------------ Epoch 278 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.512723 - Iter 024 / 025, Loss: 0.573184 * Train accuracy / confusion: 79.50% / [[264, 94], [70, 372]], * Val accuracy / confusion: 72.31% / [[136, 94], [50, 240]] ------------------------------ Epoch 279 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466666 - Iter 024 / 025, Loss: 0.436471 * Train accuracy / confusion: 77.50% / [[258, 100], [80, 362]], * Val accuracy / confusion: 72.12% / [[136, 94], [51, 239]] ------------------------------ Epoch 280 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.496707 - Iter 024 / 025, Loss: 0.461308 * Train accuracy / confusion: 78.75% / [[260, 92], [78, 370]], * Val accuracy / confusion: 71.73% / [[134, 96], [51, 239]] ------------------------------ Epoch 281 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.492914 - Iter 024 / 025, Loss: 0.345258 * Train accuracy / confusion: 78.50% / [[260, 97], [75, 368]], * Val accuracy / confusion: 70.77% / [[129, 101], [51, 239]] ------------------------------ Epoch 282 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.618673 - Iter 024 / 025, Loss: 0.467408 * Train accuracy / confusion: 79.50% / [[262, 96], [68, 374]], * Val accuracy / confusion: 72.31% / [[143, 87], [57, 233]] ------------------------------ Epoch 283 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.259856 - Iter 024 / 025, Loss: 0.327307 * Train accuracy / confusion: 80.50% / [[267, 90], [66, 377]], * Val accuracy / confusion: 68.85% / [[120, 110], [52, 238]] ------------------------------ Epoch 284 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.503285 - Iter 024 / 025, Loss: 0.472326 * Train accuracy / confusion: 79.38% / [[271, 88], [77, 364]], * Val accuracy / confusion: 71.73% / [[141, 89], [58, 232]] ------------------------------ Epoch 285 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.467555 - Iter 024 / 025, Loss: 0.494265 * Train accuracy / confusion: 79.00% / [[266, 94], [74, 366]], * Val accuracy / confusion: 69.04% / [[129, 101], [60, 230]] ------------------------------ Epoch 286 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.472840 - Iter 024 / 025, Loss: 0.451727 * Train accuracy / confusion: 77.38% / [[268, 92], [89, 351]], * Val accuracy / confusion: 67.69% / [[120, 110], [58, 232]] ------------------------------ Epoch 287 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342780 - Iter 024 / 025, Loss: 0.657337 * Train accuracy / confusion: 78.50% / [[258, 97], [75, 370]], * Val accuracy / confusion: 72.12% / [[128, 102], [43, 247]] ------------------------------ Epoch 288 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.547376 - Iter 024 / 025, Loss: 0.447337 * Train accuracy / confusion: 80.25% / [[275, 80], [78, 367]], * Val accuracy / confusion: 72.31% / [[145, 85], [59, 231]] ------------------------------ Epoch 289 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.432532 - Iter 024 / 025, Loss: 0.517851 * Train accuracy / confusion: 79.75% / [[276, 81], [81, 362]], * Val accuracy / confusion: 70.77% / [[129, 101], [51, 239]] ------------------------------ Epoch 290 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.368088 - Iter 024 / 025, Loss: 0.521613 * Train accuracy / confusion: 78.38% / [[254, 98], [75, 373]], * Val accuracy / confusion: 70.58% / [[137, 93], [60, 230]] ------------------------------ Epoch 291 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.542164 - Iter 024 / 025, Loss: 0.485634 * Train accuracy / confusion: 79.12% / [[263, 91], [76, 370]], * Val accuracy / confusion: 71.73% / [[129, 101], [46, 244]] ------------------------------ Epoch 292 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466848 - Iter 024 / 025, Loss: 0.469543 * Train accuracy / confusion: 77.62% / [[257, 98], [81, 364]], * Val accuracy / confusion: 72.31% / [[131, 99], [45, 245]] ------------------------------ Epoch 293 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.351613 - Iter 024 / 025, Loss: 0.586861 * Train accuracy / confusion: 79.62% / [[269, 87], [76, 368]], * Val accuracy / confusion: 72.12% / [[140, 90], [55, 235]] ------------------------------ Epoch 294 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.633057 - Iter 024 / 025, Loss: 0.474712 * Train accuracy / confusion: 79.38% / [[267, 89], [76, 368]], * Val accuracy / confusion: 73.27% / [[137, 93], [46, 244]] ------------------------------ Epoch 295 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.371703 - Iter 024 / 025, Loss: 0.473149 * Train accuracy / confusion: 80.88% / [[268, 86], [67, 379]], * Val accuracy / confusion: 71.15% / [[128, 102], [48, 242]] ------------------------------ Epoch 296 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.347406 - Iter 024 / 025, Loss: 0.362929 * Train accuracy / confusion: 79.12% / [[263, 94], [73, 370]], * Val accuracy / confusion: 73.08% / [[152, 78], [62, 228]] ------------------------------ Epoch 297 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.402661 - Iter 024 / 025, Loss: 0.302245 * Train accuracy / confusion: 79.62% / [[261, 97], [66, 376]], * Val accuracy / confusion: 69.42% / [[117, 113], [46, 244]] ------------------------------ Epoch 298 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.424933 - Iter 024 / 025, Loss: 0.502713 * Train accuracy / confusion: 78.50% / [[256, 97], [75, 372]], * Val accuracy / confusion: 70.19% / [[134, 96], [59, 231]] ------------------------------ Epoch 299 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.523340 - Iter 024 / 025, Loss: 0.513851 * Train accuracy / confusion: 81.12% / [[262, 89], [62, 387]], * Val accuracy / confusion: 71.73% / [[142, 88], [59, 231]] ------------------------------ Epoch 300 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.470525 - Iter 024 / 025, Loss: 0.479483 * Train accuracy / confusion: 79.50% / [[265, 91], [73, 371]], * Val accuracy / confusion: 72.31% / [[136, 94], [50, 240]] ------------------------------ Epoch 301 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.529169 - Iter 024 / 025, Loss: 0.381523 * Train accuracy / confusion: 78.50% / [[258, 97], [75, 370]], * Val accuracy / confusion: 69.23% / [[125, 105], [55, 235]] ------------------------------ Epoch 302 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.501477 - Iter 024 / 025, Loss: 0.517923 * Train accuracy / confusion: 78.38% / [[259, 98], [75, 368]], * Val accuracy / confusion: 72.69% / [[147, 83], [59, 231]] ------------------------------ Epoch 303 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.352356 - Iter 024 / 025, Loss: 0.492297 * Train accuracy / confusion: 76.75% / [[253, 104], [82, 361]], * Val accuracy / confusion: 71.15% / [[129, 101], [49, 241]] ------------------------------ Epoch 304 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.389608 - Iter 024 / 025, Loss: 0.427442 * Train accuracy / confusion: 78.38% / [[263, 90], [83, 364]], * Val accuracy / confusion: 69.04% / [[111, 119], [42, 248]] ------------------------------ Epoch 305 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.387918 - Iter 024 / 025, Loss: 0.607616 * Train accuracy / confusion: 79.00% / [[268, 91], [77, 364]], * Val accuracy / confusion: 69.62% / [[125, 105], [53, 237]] ------------------------------ Epoch 306 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.278966 - Iter 024 / 025, Loss: 0.598744 * Train accuracy / confusion: 79.62% / [[267, 91], [72, 370]], * Val accuracy / confusion: 72.69% / [[149, 81], [61, 229]] ------------------------------ Epoch 307 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.604599 - Iter 024 / 025, Loss: 0.355431 * Train accuracy / confusion: 81.00% / [[269, 85], [67, 379]], * Val accuracy / confusion: 73.27% / [[142, 88], [51, 239]] ------------------------------ Epoch 308 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.333051 - Iter 024 / 025, Loss: 0.721536 * Train accuracy / confusion: 79.75% / [[266, 92], [70, 372]], * Val accuracy / confusion: 69.04% / [[124, 106], [55, 235]] ------------------------------ Epoch 309 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.466150 - Iter 024 / 025, Loss: 0.639050 * Train accuracy / confusion: 78.62% / [[257, 96], [75, 372]], * Val accuracy / confusion: 70.38% / [[128, 102], [52, 238]] ------------------------------ Epoch 310 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.306743 - Iter 024 / 025, Loss: 0.537433 * Train accuracy / confusion: 79.25% / [[268, 94], [72, 366]], * Val accuracy / confusion: 70.00% / [[126, 104], [52, 238]] ------------------------------ Epoch 311 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.403641 - Iter 024 / 025, Loss: 0.542667 * Train accuracy / confusion: 79.00% / [[255, 101], [67, 377]], * Val accuracy / confusion: 71.73% / [[135, 95], [52, 238]] ------------------------------ Epoch 312 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.499621 - Iter 024 / 025, Loss: 0.420518 * Train accuracy / confusion: 78.25% / [[259, 96], [78, 367]], * Val accuracy / confusion: 72.12% / [[140, 90], [55, 235]] ------------------------------ Epoch 313 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.594112 - Iter 024 / 025, Loss: 0.345802 * Train accuracy / confusion: 79.12% / [[265, 90], [77, 368]], * Val accuracy / confusion: 70.96% / [[131, 99], [52, 238]] ------------------------------ Epoch 314 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.319002 - Iter 024 / 025, Loss: 0.336371 * Train accuracy / confusion: 78.75% / [[260, 90], [80, 370]], * Val accuracy / confusion: 72.69% / [[140, 90], [52, 238]] ------------------------------ Epoch 315 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.320670 - Iter 024 / 025, Loss: 0.300522 * Train accuracy / confusion: 79.88% / [[268, 89], [72, 371]], * Val accuracy / confusion: 70.19% / [[131, 99], [56, 234]] ------------------------------ Epoch 316 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.387494 - Iter 024 / 025, Loss: 0.314233 * Train accuracy / confusion: 80.00% / [[263, 97], [63, 377]], * Val accuracy / confusion: 69.42% / [[118, 112], [47, 243]] ------------------------------ Epoch 317 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.503971 - Iter 024 / 025, Loss: 0.649957 * Train accuracy / confusion: 79.00% / [[263, 93], [75, 369]], * Val accuracy / confusion: 71.15% / [[135, 95], [55, 235]] ------------------------------ Epoch 318 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.354913 - Iter 024 / 025, Loss: 0.523382 * Train accuracy / confusion: 79.38% / [[264, 88], [77, 371]], * Val accuracy / confusion: 72.12% / [[136, 94], [51, 239]] ------------------------------ Epoch 319 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.421740 - Iter 024 / 025, Loss: 0.348681 * Train accuracy / confusion: 79.88% / [[270, 85], [76, 369]], * Val accuracy / confusion: 71.15% / [[140, 90], [60, 230]] ------------------------------ Epoch 320 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.346164 - Iter 024 / 025, Loss: 0.365758 * Train accuracy / confusion: 78.00% / [[258, 100], [76, 366]], * Val accuracy / confusion: 73.08% / [[151, 79], [61, 229]] ------------------------------ Epoch 321 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.389391 - Iter 024 / 025, Loss: 0.564885 * Train accuracy / confusion: 80.75% / [[270, 84], [70, 376]], * Val accuracy / confusion: 68.65% / [[123, 107], [56, 234]] ------------------------------ Epoch 322 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.291995 - Iter 024 / 025, Loss: 0.424364 * Train accuracy / confusion: 76.88% / [[260, 100], [85, 355]], * Val accuracy / confusion: 71.54% / [[166, 64], [84, 206]] ------------------------------ Epoch 323 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.382558 - Iter 024 / 025, Loss: 0.331348 * Train accuracy / confusion: 78.88% / [[261, 94], [75, 370]], * Val accuracy / confusion: 70.58% / [[133, 97], [56, 234]] ------------------------------ Epoch 324 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.385514 - Iter 024 / 025, Loss: 0.429861 * Train accuracy / confusion: 79.50% / [[265, 92], [72, 371]], * Val accuracy / confusion: 70.96% / [[133, 97], [54, 236]] ------------------------------ Epoch 325 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.517087 - Iter 024 / 025, Loss: 0.498053 * Train accuracy / confusion: 78.88% / [[261, 98], [71, 370]], * Val accuracy / confusion: 72.31% / [[133, 97], [47, 243]] ------------------------------ Epoch 326 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.407033 - Iter 024 / 025, Loss: 0.395741 * Train accuracy / confusion: 78.62% / [[258, 99], [72, 371]], * Val accuracy / confusion: 71.15% / [[122, 108], [42, 248]] ------------------------------ Epoch 327 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.444139 - Iter 024 / 025, Loss: 0.404961 * Train accuracy / confusion: 80.25% / [[266, 91], [67, 376]], * Val accuracy / confusion: 69.81% / [[130, 100], [57, 233]] ------------------------------ Epoch 328 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.532901 - Iter 024 / 025, Loss: 0.330764 * Train accuracy / confusion: 79.00% / [[257, 97], [71, 375]], * Val accuracy / confusion: 72.31% / [[147, 83], [61, 229]] ------------------------------ Epoch 329 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.681361 - Iter 024 / 025, Loss: 0.443372 * Train accuracy / confusion: 79.00% / [[264, 87], [81, 368]], * Val accuracy / confusion: 70.19% / [[122, 108], [47, 243]] ------------------------------ Epoch 330 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.513145 - Iter 024 / 025, Loss: 0.354712 * Train accuracy / confusion: 79.38% / [[264, 92], [73, 371]], * Val accuracy / confusion: 71.73% / [[143, 87], [60, 230]] ------------------------------ Epoch 331 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.516059 - Iter 024 / 025, Loss: 0.414662 * Train accuracy / confusion: 78.25% / [[256, 104], [70, 370]], * Val accuracy / confusion: 70.19% / [[133, 97], [58, 232]] ------------------------------ Epoch 332 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.394130 - Iter 024 / 025, Loss: 0.528113 * Train accuracy / confusion: 79.50% / [[256, 98], [66, 380]], * Val accuracy / confusion: 73.65% / [[142, 88], [49, 241]] ------------------------------ Epoch 333 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.338314 - Iter 024 / 025, Loss: 0.562861 * Train accuracy / confusion: 79.25% / [[255, 99], [67, 379]], * Val accuracy / confusion: 70.19% / [[115, 115], [40, 250]] ------------------------------ Epoch 334 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357496 - Iter 024 / 025, Loss: 0.364732 * Train accuracy / confusion: 80.38% / [[262, 92], [65, 381]], * Val accuracy / confusion: 72.31% / [[135, 95], [49, 241]] ------------------------------ Epoch 335 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.372954 - Iter 024 / 025, Loss: 0.742270 * Train accuracy / confusion: 78.12% / [[255, 98], [77, 370]], * Val accuracy / confusion: 70.96% / [[127, 103], [48, 242]] ------------------------------ Epoch 336 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.364780 - Iter 024 / 025, Loss: 0.544228 * Train accuracy / confusion: 79.25% / [[265, 92], [74, 369]], * Val accuracy / confusion: 70.58% / [[114, 116], [37, 253]] ------------------------------ Epoch 337 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.521745 - Iter 024 / 025, Loss: 0.411238 * Train accuracy / confusion: 79.00% / [[262, 94], [74, 370]], * Val accuracy / confusion: 69.81% / [[134, 96], [61, 229]] ------------------------------ Epoch 338 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.472129 - Iter 024 / 025, Loss: 0.398908 * Train accuracy / confusion: 79.88% / [[260, 97], [64, 379]], * Val accuracy / confusion: 69.23% / [[125, 105], [55, 235]] ------------------------------ Epoch 339 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.544626 - Iter 024 / 025, Loss: 0.306366 * Train accuracy / confusion: 79.88% / [[266, 88], [73, 373]], * Val accuracy / confusion: 72.69% / [[140, 90], [52, 238]] ------------------------------ Epoch 340 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.444761 - Iter 024 / 025, Loss: 0.503731 * Train accuracy / confusion: 77.88% / [[249, 105], [72, 374]], * Val accuracy / confusion: 71.73% / [[127, 103], [44, 246]] ------------------------------ Epoch 341 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408702 - Iter 024 / 025, Loss: 0.295044 * Train accuracy / confusion: 80.12% / [[257, 92], [67, 384]], * Val accuracy / confusion: 68.46% / [[113, 117], [47, 243]] ------------------------------ Epoch 342 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.385597 - Iter 024 / 025, Loss: 0.484086 * Train accuracy / confusion: 79.62% / [[257, 99], [64, 380]], * Val accuracy / confusion: 69.23% / [[126, 104], [56, 234]] ------------------------------ Epoch 343 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.370135 - Iter 024 / 025, Loss: 0.471924 * Train accuracy / confusion: 77.88% / [[254, 102], [75, 369]], * Val accuracy / confusion: 65.77% / [[101, 129], [49, 241]] ------------------------------ Epoch 344 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.402186 - Iter 024 / 025, Loss: 0.540393 * Train accuracy / confusion: 79.38% / [[265, 95], [70, 370]], * Val accuracy / confusion: 67.88% / [[120, 110], [57, 233]] ------------------------------ Epoch 345 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.354907 - Iter 024 / 025, Loss: 0.831802 * Train accuracy / confusion: 80.62% / [[268, 89], [66, 377]], * Val accuracy / confusion: 71.35% / [[139, 91], [58, 232]] ------------------------------ Epoch 346 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.537492 - Iter 024 / 025, Loss: 0.491168 * Train accuracy / confusion: 77.50% / [[253, 105], [75, 367]], * Val accuracy / confusion: 70.96% / [[126, 104], [47, 243]] ------------------------------ Epoch 347 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.412376 - Iter 024 / 025, Loss: 0.412083 * Train accuracy / confusion: 80.50% / [[259, 95], [61, 385]], * Val accuracy / confusion: 69.81% / [[129, 101], [56, 234]] ------------------------------ Epoch 348 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.486682 - Iter 024 / 025, Loss: 0.360143 * Train accuracy / confusion: 78.62% / [[259, 96], [75, 370]], * Val accuracy / confusion: 70.58% / [[125, 105], [48, 242]] ------------------------------ Epoch 349 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.463539 - Iter 024 / 025, Loss: 0.429018 * Train accuracy / confusion: 78.88% / [[267, 94], [75, 364]], * Val accuracy / confusion: 69.81% / [[116, 114], [43, 247]] ------------------------------ Epoch 350 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.389186 - Iter 024 / 025, Loss: 0.499224 * Train accuracy / confusion: 78.75% / [[258, 100], [70, 372]], * Val accuracy / confusion: 72.69% / [[135, 95], [47, 243]] ------------------------------ Epoch 351 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.399027 - Iter 024 / 025, Loss: 0.604524 * Train accuracy / confusion: 79.75% / [[263, 98], [64, 375]], * Val accuracy / confusion: 68.08% / [[111, 119], [47, 243]] ------------------------------ Epoch 352 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.458092 - Iter 024 / 025, Loss: 0.346702 * Train accuracy / confusion: 77.62% / [[255, 102], [77, 366]], * Val accuracy / confusion: 73.08% / [[129, 101], [39, 251]] ------------------------------ Epoch 353 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.451636 - Iter 024 / 025, Loss: 0.398395 * Train accuracy / confusion: 80.12% / [[265, 94], [65, 376]], * Val accuracy / confusion: 73.08% / [[158, 72], [68, 222]] ------------------------------ Epoch 354 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.519936 - Iter 024 / 025, Loss: 0.469801 * Train accuracy / confusion: 80.00% / [[270, 90], [70, 370]], * Val accuracy / confusion: 70.96% / [[137, 93], [58, 232]] ------------------------------ Epoch 355 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.297911 - Iter 024 / 025, Loss: 0.321871 * Train accuracy / confusion: 80.25% / [[268, 90], [68, 374]], * Val accuracy / confusion: 71.92% / [[136, 94], [52, 238]] ------------------------------ Epoch 356 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.605027 - Iter 024 / 025, Loss: 0.553072 * Train accuracy / confusion: 79.50% / [[264, 88], [76, 372]], * Val accuracy / confusion: 72.69% / [[135, 95], [47, 243]] ------------------------------ Epoch 357 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.618405 - Iter 024 / 025, Loss: 0.394995 * Train accuracy / confusion: 78.62% / [[260, 92], [79, 369]], * Val accuracy / confusion: 71.73% / [[136, 94], [53, 237]] ------------------------------ Epoch 358 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.673723 - Iter 024 / 025, Loss: 0.395940 * Train accuracy / confusion: 79.38% / [[262, 87], [78, 373]], * Val accuracy / confusion: 70.38% / [[123, 107], [47, 243]] ------------------------------ Epoch 359 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.397822 - Iter 024 / 025, Loss: 0.603506 * Train accuracy / confusion: 79.12% / [[253, 95], [72, 380]], * Val accuracy / confusion: 71.15% / [[131, 99], [51, 239]] ------------------------------ Epoch 360 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.438844 - Iter 024 / 025, Loss: 0.379809 * Train accuracy / confusion: 78.00% / [[256, 98], [78, 368]], * Val accuracy / confusion: 70.77% / [[131, 99], [53, 237]] ------------------------------ Epoch 361 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.362207 - Iter 024 / 025, Loss: 0.615981 * Train accuracy / confusion: 79.00% / [[253, 97], [71, 379]], * Val accuracy / confusion: 72.31% / [[147, 83], [61, 229]] ------------------------------ Epoch 362 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.598075 - Iter 024 / 025, Loss: 0.458608 * Train accuracy / confusion: 77.12% / [[252, 109], [74, 365]], * Val accuracy / confusion: 67.31% / [[101, 129], [41, 249]] ------------------------------ Epoch 363 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.467209 - Iter 024 / 025, Loss: 0.538450 * Train accuracy / confusion: 80.00% / [[253, 96], [64, 387]], * Val accuracy / confusion: 72.31% / [[148, 82], [62, 228]] ------------------------------ Epoch 364 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.503464 - Iter 024 / 025, Loss: 0.559066 * Train accuracy / confusion: 80.00% / [[268, 91], [69, 372]], * Val accuracy / confusion: 70.77% / [[121, 109], [43, 247]] ------------------------------ Epoch 365 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.405136 - Iter 024 / 025, Loss: 0.365041 * Train accuracy / confusion: 81.38% / [[267, 91], [58, 384]], * Val accuracy / confusion: 71.15% / [[134, 96], [54, 236]] ------------------------------ Epoch 366 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.793622 - Iter 024 / 025, Loss: 0.340655 * Train accuracy / confusion: 77.50% / [[249, 108], [72, 371]], * Val accuracy / confusion: 72.69% / [[138, 92], [50, 240]] ------------------------------ Epoch 367 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.541514 - Iter 024 / 025, Loss: 0.385242 * Train accuracy / confusion: 81.00% / [[267, 85], [67, 381]], * Val accuracy / confusion: 71.73% / [[139, 91], [56, 234]] ------------------------------ Epoch 368 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.545295 - Iter 024 / 025, Loss: 0.415025 * Train accuracy / confusion: 79.75% / [[258, 98], [64, 380]], * Val accuracy / confusion: 70.77% / [[126, 104], [48, 242]] ------------------------------ Epoch 369 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.385053 - Iter 024 / 025, Loss: 0.461516 * Train accuracy / confusion: 80.12% / [[269, 91], [68, 372]], * Val accuracy / confusion: 71.54% / [[125, 105], [43, 247]] ------------------------------ Epoch 370 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.371022 - Iter 024 / 025, Loss: 0.471051 * Train accuracy / confusion: 80.25% / [[267, 88], [70, 375]], * Val accuracy / confusion: 70.96% / [[137, 93], [58, 232]] ------------------------------ Epoch 371 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.325929 - Iter 024 / 025, Loss: 0.334260 * Train accuracy / confusion: 79.00% / [[259, 96], [72, 373]], * Val accuracy / confusion: 71.35% / [[128, 102], [47, 243]] ------------------------------ Epoch 372 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.479606 - Iter 024 / 025, Loss: 0.424576 * Train accuracy / confusion: 80.12% / [[270, 93], [66, 371]], * Val accuracy / confusion: 68.27% / [[120, 110], [55, 235]] ------------------------------ Epoch 373 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.344292 - Iter 024 / 025, Loss: 0.427621 * Train accuracy / confusion: 81.12% / [[269, 81], [70, 380]], * Val accuracy / confusion: 69.04% / [[119, 111], [50, 240]] ------------------------------ Epoch 374 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.469735 - Iter 024 / 025, Loss: 0.285247 * Train accuracy / confusion: 78.50% / [[255, 104], [68, 373]], * Val accuracy / confusion: 70.58% / [[134, 96], [57, 233]] ------------------------------ Epoch 375 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.505968 - Iter 024 / 025, Loss: 0.346664 * Train accuracy / confusion: 78.75% / [[262, 94], [76, 368]], * Val accuracy / confusion: 70.00% / [[131, 99], [57, 233]] ------------------------------ Epoch 376 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.563087 - Iter 024 / 025, Loss: 0.455961 * Train accuracy / confusion: 77.38% / [[255, 98], [83, 364]], * Val accuracy / confusion: 71.92% / [[138, 92], [54, 236]] ------------------------------ Epoch 377 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.439668 - Iter 024 / 025, Loss: 0.316828 * Train accuracy / confusion: 79.50% / [[258, 99], [65, 378]], * Val accuracy / confusion: 70.38% / [[122, 108], [46, 244]] ------------------------------ Epoch 378 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.485974 - Iter 024 / 025, Loss: 0.788947 * Train accuracy / confusion: 77.75% / [[255, 100], [78, 367]], * Val accuracy / confusion: 71.73% / [[134, 96], [51, 239]] ------------------------------ Epoch 379 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.319134 - Iter 024 / 025, Loss: 0.549636 * Train accuracy / confusion: 77.62% / [[263, 97], [82, 358]], * Val accuracy / confusion: 74.42% / [[139, 91], [42, 248]] ------------------------------ Epoch 380 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.371781 - Iter 024 / 025, Loss: 0.674434 * Train accuracy / confusion: 76.88% / [[246, 108], [77, 369]], * Val accuracy / confusion: 70.77% / [[121, 109], [43, 247]] ------------------------------ Epoch 381 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.293366 - Iter 024 / 025, Loss: 0.369627 * Train accuracy / confusion: 80.38% / [[263, 90], [67, 380]], * Val accuracy / confusion: 73.27% / [[141, 89], [50, 240]] ------------------------------ Epoch 382 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.337318 - Iter 024 / 025, Loss: 0.267722 * Train accuracy / confusion: 81.12% / [[272, 84], [67, 377]], * Val accuracy / confusion: 72.50% / [[146, 84], [59, 231]] ------------------------------ Epoch 383 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408341 - Iter 024 / 025, Loss: 0.345308 * Train accuracy / confusion: 79.00% / [[259, 95], [73, 373]], * Val accuracy / confusion: 70.38% / [[128, 102], [52, 238]] ------------------------------ Epoch 384 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.396659 - Iter 024 / 025, Loss: 0.379509 * Train accuracy / confusion: 77.62% / [[260, 97], [82, 361]], * Val accuracy / confusion: 72.69% / [[140, 90], [52, 238]] ------------------------------ Epoch 385 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.585779 - Iter 024 / 025, Loss: 0.315115 * Train accuracy / confusion: 82.00% / [[275, 79], [65, 381]], * Val accuracy / confusion: 72.12% / [[145, 85], [60, 230]] ------------------------------ Epoch 386 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.447919 - Iter 024 / 025, Loss: 0.389200 * Train accuracy / confusion: 80.25% / [[261, 88], [70, 381]], * Val accuracy / confusion: 69.23% / [[111, 119], [41, 249]] ------------------------------ Epoch 387 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.465085 - Iter 024 / 025, Loss: 0.399790 * Train accuracy / confusion: 79.00% / [[254, 102], [66, 378]], * Val accuracy / confusion: 69.42% / [[122, 108], [51, 239]] ------------------------------ Epoch 388 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.377992 - Iter 024 / 025, Loss: 0.403194 * Train accuracy / confusion: 79.75% / [[255, 99], [63, 383]], * Val accuracy / confusion: 71.15% / [[129, 101], [49, 241]] ------------------------------ Epoch 389 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.557674 - Iter 024 / 025, Loss: 0.411709 * Train accuracy / confusion: 78.12% / [[257, 102], [73, 368]], * Val accuracy / confusion: 72.50% / [[149, 81], [62, 228]] ------------------------------ Epoch 390 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342755 - Iter 024 / 025, Loss: 0.540743 * Train accuracy / confusion: 78.12% / [[250, 110], [65, 375]], * Val accuracy / confusion: 70.19% / [[136, 94], [61, 229]] ------------------------------ Epoch 391 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.544732 - Iter 024 / 025, Loss: 0.313505 * Train accuracy / confusion: 79.38% / [[262, 97], [68, 373]], * Val accuracy / confusion: 72.69% / [[143, 87], [55, 235]] ------------------------------ Epoch 392 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.312058 - Iter 024 / 025, Loss: 0.411297 * Train accuracy / confusion: 80.38% / [[267, 88], [69, 376]], * Val accuracy / confusion: 70.38% / [[139, 91], [63, 227]] ------------------------------ Epoch 393 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.484936 - Iter 024 / 025, Loss: 0.575121 * Train accuracy / confusion: 81.12% / [[266, 89], [62, 383]], * Val accuracy / confusion: 68.27% / [[127, 103], [62, 228]] ------------------------------ Epoch 394 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.452903 - Iter 024 / 025, Loss: 0.363160 * Train accuracy / confusion: 78.62% / [[257, 97], [74, 372]], * Val accuracy / confusion: 70.38% / [[137, 93], [61, 229]] ------------------------------ Epoch 395 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.386399 - Iter 024 / 025, Loss: 0.532920 * Train accuracy / confusion: 79.25% / [[261, 93], [73, 373]], * Val accuracy / confusion: 70.77% / [[140, 90], [62, 228]] ------------------------------ Epoch 396 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.370861 - Iter 024 / 025, Loss: 0.370999 * Train accuracy / confusion: 80.50% / [[266, 87], [69, 378]], * Val accuracy / confusion: 69.81% / [[128, 102], [55, 235]] ------------------------------ Epoch 397 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.384025 - Iter 024 / 025, Loss: 0.557049 * Train accuracy / confusion: 79.25% / [[264, 92], [74, 370]], * Val accuracy / confusion: 71.35% / [[150, 80], [69, 221]] ------------------------------ Epoch 398 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.397620 - Iter 024 / 025, Loss: 0.476728 * Train accuracy / confusion: 79.25% / [[266, 92], [74, 368]], * Val accuracy / confusion: 71.35% / [[149, 81], [68, 222]] ------------------------------ Epoch 399 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.559142 - Iter 024 / 025, Loss: 0.451182 * Train accuracy / confusion: 78.62% / [[263, 93], [78, 366]], * Val accuracy / confusion: 69.23% / [[136, 94], [66, 224]] ------------------------------ Epoch 400 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.388971 - Iter 024 / 025, Loss: 0.595207 * Train accuracy / confusion: 79.50% / [[267, 93], [71, 369]], * Val accuracy / confusion: 69.62% / [[139, 91], [67, 223]] ------------------------------ Epoch 401 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.340902 - Iter 024 / 025, Loss: 0.541778 * Train accuracy / confusion: 77.38% / [[255, 99], [82, 364]], * Val accuracy / confusion: 69.23% / [[134, 96], [64, 226]] ------------------------------ Epoch 402 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.658965 - Iter 024 / 025, Loss: 0.440007 * Train accuracy / confusion: 79.00% / [[264, 97], [71, 368]], * Val accuracy / confusion: 74.23% / [[143, 87], [47, 243]] ------------------------------ Epoch 403 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.464230 - Iter 024 / 025, Loss: 0.447556 * Train accuracy / confusion: 78.12% / [[260, 92], [83, 365]], * Val accuracy / confusion: 69.62% / [[125, 105], [53, 237]] ------------------------------ Epoch 404 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.481748 - Iter 024 / 025, Loss: 0.727988 * Train accuracy / confusion: 80.00% / [[269, 86], [74, 371]], * Val accuracy / confusion: 71.73% / [[136, 94], [53, 237]] ------------------------------ Epoch 405 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.510591 - Iter 024 / 025, Loss: 0.531127 * Train accuracy / confusion: 80.38% / [[264, 93], [64, 379]], * Val accuracy / confusion: 73.85% / [[150, 80], [56, 234]] ------------------------------ Epoch 406 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.490681 - Iter 024 / 025, Loss: 0.454691 * Train accuracy / confusion: 78.62% / [[260, 92], [79, 369]], * Val accuracy / confusion: 70.19% / [[137, 93], [62, 228]] ------------------------------ Epoch 407 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.381190 - Iter 024 / 025, Loss: 0.478117 * Train accuracy / confusion: 78.62% / [[260, 99], [72, 369]], * Val accuracy / confusion: 70.58% / [[138, 92], [61, 229]] ------------------------------ Epoch 408 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.475991 - Iter 024 / 025, Loss: 0.423490 * Train accuracy / confusion: 81.50% / [[267, 93], [55, 385]], * Val accuracy / confusion: 71.15% / [[142, 88], [62, 228]] ------------------------------ Epoch 409 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.461394 - Iter 024 / 025, Loss: 0.651362 * Train accuracy / confusion: 81.62% / [[276, 75], [72, 377]], * Val accuracy / confusion: 71.73% / [[147, 83], [64, 226]] ------------------------------ Epoch 410 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.309195 - Iter 024 / 025, Loss: 0.346973 * Train accuracy / confusion: 81.75% / [[272, 80], [66, 382]], * Val accuracy / confusion: 70.77% / [[141, 89], [63, 227]] ------------------------------ Epoch 411 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.519349 - Iter 024 / 025, Loss: 0.398330 * Train accuracy / confusion: 78.50% / [[256, 102], [70, 372]], * Val accuracy / confusion: 71.54% / [[137, 93], [55, 235]] ------------------------------ Epoch 412 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.402552 - Iter 024 / 025, Loss: 0.434361 * Train accuracy / confusion: 80.50% / [[273, 85], [71, 371]], * Val accuracy / confusion: 70.38% / [[128, 102], [52, 238]] ------------------------------ Epoch 413 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.331065 - Iter 024 / 025, Loss: 0.368437 * Train accuracy / confusion: 80.75% / [[265, 87], [67, 381]], * Val accuracy / confusion: 69.23% / [[124, 106], [54, 236]] ------------------------------ Epoch 414 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.496825 - Iter 024 / 025, Loss: 0.527149 * Train accuracy / confusion: 81.12% / [[273, 82], [69, 376]], * Val accuracy / confusion: 71.92% / [[145, 85], [61, 229]] ------------------------------ Epoch 415 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.554152 - Iter 024 / 025, Loss: 0.455878 * Train accuracy / confusion: 80.25% / [[270, 88], [70, 372]], * Val accuracy / confusion: 69.81% / [[134, 96], [61, 229]] ------------------------------ Epoch 416 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.508580 - Iter 024 / 025, Loss: 0.391728 * Train accuracy / confusion: 79.00% / [[264, 95], [73, 368]], * Val accuracy / confusion: 70.00% / [[137, 93], [63, 227]] ------------------------------ Epoch 417 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.416799 - Iter 024 / 025, Loss: 0.318629 * Train accuracy / confusion: 80.12% / [[266, 87], [72, 375]], * Val accuracy / confusion: 71.35% / [[134, 96], [53, 237]] ------------------------------ Epoch 418 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.370185 - Iter 024 / 025, Loss: 0.520375 * Train accuracy / confusion: 79.62% / [[261, 97], [66, 376]], * Val accuracy / confusion: 73.08% / [[135, 95], [45, 245]] ------------------------------ Epoch 419 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.361552 - Iter 024 / 025, Loss: 0.282175 * Train accuracy / confusion: 79.38% / [[262, 98], [67, 373]], * Val accuracy / confusion: 69.81% / [[133, 97], [60, 230]] ------------------------------ Epoch 420 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.607509 - Iter 024 / 025, Loss: 0.443281 * Train accuracy / confusion: 82.88% / [[282, 74], [63, 381]], * Val accuracy / confusion: 70.38% / [[134, 96], [58, 232]] ------------------------------ Epoch 421 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.492159 - Iter 024 / 025, Loss: 0.580477 * Train accuracy / confusion: 81.25% / [[278, 79], [71, 372]], * Val accuracy / confusion: 69.23% / [[127, 103], [57, 233]] ------------------------------ Epoch 422 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.390233 - Iter 024 / 025, Loss: 0.302928 * Train accuracy / confusion: 79.88% / [[258, 96], [65, 381]], * Val accuracy / confusion: 71.73% / [[134, 96], [51, 239]] ------------------------------ Epoch 423 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.321458 - Iter 024 / 025, Loss: 0.466362 * Train accuracy / confusion: 81.38% / [[266, 90], [59, 385]], * Val accuracy / confusion: 72.50% / [[141, 89], [54, 236]] ------------------------------ Epoch 424 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.390015 - Iter 024 / 025, Loss: 0.602791 * Train accuracy / confusion: 80.88% / [[271, 89], [64, 376]], * Val accuracy / confusion: 69.81% / [[135, 95], [62, 228]] ------------------------------ Epoch 425 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.427494 - Iter 024 / 025, Loss: 0.407155 * Train accuracy / confusion: 79.50% / [[268, 90], [74, 368]], * Val accuracy / confusion: 69.62% / [[121, 109], [49, 241]] ------------------------------ Epoch 426 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.348628 - Iter 024 / 025, Loss: 0.626237 * Train accuracy / confusion: 79.50% / [[264, 91], [73, 372]], * Val accuracy / confusion: 69.81% / [[126, 104], [53, 237]] ------------------------------ Epoch 427 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.498559 - Iter 024 / 025, Loss: 0.438958 * Train accuracy / confusion: 81.62% / [[267, 89], [58, 386]], * Val accuracy / confusion: 68.46% / [[122, 108], [56, 234]] ------------------------------ Epoch 428 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.359352 - Iter 024 / 025, Loss: 0.482842 * Train accuracy / confusion: 81.75% / [[275, 80], [66, 379]], * Val accuracy / confusion: 68.46% / [[126, 104], [60, 230]] ------------------------------ Epoch 429 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.412945 - Iter 024 / 025, Loss: 0.492031 * Train accuracy / confusion: 82.38% / [[277, 82], [59, 382]], * Val accuracy / confusion: 69.42% / [[133, 97], [62, 228]] ------------------------------ Epoch 430 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.470427 - Iter 024 / 025, Loss: 0.520437 * Train accuracy / confusion: 79.50% / [[272, 86], [78, 364]], * Val accuracy / confusion: 71.15% / [[139, 91], [59, 231]] ------------------------------ Epoch 431 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.526568 - Iter 024 / 025, Loss: 0.250529 * Train accuracy / confusion: 79.50% / [[261, 95], [69, 375]], * Val accuracy / confusion: 68.27% / [[124, 106], [59, 231]] ------------------------------ Epoch 432 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.385008 - Iter 024 / 025, Loss: 0.658844 * Train accuracy / confusion: 81.00% / [[274, 78], [74, 374]], * Val accuracy / confusion: 72.69% / [[146, 84], [58, 232]] ------------------------------ Epoch 433 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.358945 - Iter 024 / 025, Loss: 0.410823 * Train accuracy / confusion: 79.12% / [[257, 100], [67, 376]], * Val accuracy / confusion: 71.35% / [[139, 91], [58, 232]] ------------------------------ Epoch 434 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.504273 - Iter 024 / 025, Loss: 0.348927 * Train accuracy / confusion: 79.88% / [[263, 93], [68, 376]], * Val accuracy / confusion: 70.58% / [[131, 99], [54, 236]] ------------------------------ Epoch 435 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.364020 - Iter 024 / 025, Loss: 0.528536 * Train accuracy / confusion: 80.00% / [[261, 93], [67, 379]], * Val accuracy / confusion: 70.58% / [[131, 99], [54, 236]] ------------------------------ Epoch 436 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.398738 - Iter 024 / 025, Loss: 0.352077 * Train accuracy / confusion: 80.12% / [[268, 92], [67, 373]], * Val accuracy / confusion: 71.92% / [[136, 94], [52, 238]] ------------------------------ Epoch 437 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.535271 - Iter 024 / 025, Loss: 0.287947 * Train accuracy / confusion: 79.88% / [[272, 87], [74, 367]], * Val accuracy / confusion: 69.62% / [[132, 98], [60, 230]] ------------------------------ Epoch 438 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.424939 - Iter 024 / 025, Loss: 0.401276 * Train accuracy / confusion: 79.50% / [[268, 93], [71, 368]], * Val accuracy / confusion: 68.27% / [[131, 99], [66, 224]] ------------------------------ Epoch 439 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.434362 - Iter 024 / 025, Loss: 0.338995 * Train accuracy / confusion: 80.25% / [[271, 90], [68, 371]], * Val accuracy / confusion: 68.27% / [[122, 108], [57, 233]] ------------------------------ Epoch 440 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.252674 - Iter 024 / 025, Loss: 0.364388 * Train accuracy / confusion: 81.62% / [[270, 84], [63, 383]], * Val accuracy / confusion: 69.23% / [[123, 107], [53, 237]] ------------------------------ Epoch 441 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.728501 - Iter 024 / 025, Loss: 0.340030 * Train accuracy / confusion: 79.88% / [[269, 91], [70, 370]], * Val accuracy / confusion: 72.12% / [[144, 86], [59, 231]] ------------------------------ Epoch 442 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.397711 - Iter 024 / 025, Loss: 0.397828 * Train accuracy / confusion: 79.62% / [[266, 93], [70, 371]], * Val accuracy / confusion: 70.58% / [[143, 87], [66, 224]] ------------------------------ Epoch 443 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.451093 - Iter 024 / 025, Loss: 0.509954 * Train accuracy / confusion: 80.12% / [[269, 86], [73, 372]], * Val accuracy / confusion: 70.38% / [[135, 95], [59, 231]] ------------------------------ Epoch 444 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.496868 - Iter 024 / 025, Loss: 0.384247 * Train accuracy / confusion: 79.12% / [[261, 93], [74, 372]], * Val accuracy / confusion: 71.54% / [[128, 102], [46, 244]] ------------------------------ Epoch 445 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.585162 - Iter 024 / 025, Loss: 0.464368 * Train accuracy / confusion: 79.38% / [[261, 97], [68, 374]], * Val accuracy / confusion: 67.31% / [[117, 113], [57, 233]] ------------------------------ Epoch 446 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.531274 - Iter 024 / 025, Loss: 0.372280 * Train accuracy / confusion: 78.12% / [[255, 101], [74, 370]], * Val accuracy / confusion: 71.54% / [[134, 96], [52, 238]] ------------------------------ Epoch 447 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.453202 - Iter 024 / 025, Loss: 0.460446 * Train accuracy / confusion: 80.88% / [[267, 89], [64, 380]], * Val accuracy / confusion: 69.81% / [[128, 102], [55, 235]] ------------------------------ Epoch 448 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.395747 - Iter 024 / 025, Loss: 0.450160 * Train accuracy / confusion: 78.12% / [[257, 100], [75, 368]], * Val accuracy / confusion: 67.69% / [[123, 107], [61, 229]] ------------------------------ Epoch 449 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.629066 - Iter 024 / 025, Loss: 0.393274 * Train accuracy / confusion: 80.88% / [[269, 89], [64, 378]], * Val accuracy / confusion: 70.96% / [[134, 96], [55, 235]] ------------------------------ Epoch 450 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.460525 - Iter 024 / 025, Loss: 0.522710 * Train accuracy / confusion: 79.88% / [[262, 90], [71, 377]], * Val accuracy / confusion: 68.85% / [[129, 101], [61, 229]] ------------------------------ Epoch 451 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.575875 - Iter 024 / 025, Loss: 0.500063 * Train accuracy / confusion: 80.62% / [[266, 94], [61, 379]], * Val accuracy / confusion: 69.62% / [[131, 99], [59, 231]] ------------------------------ Epoch 452 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.409349 - Iter 024 / 025, Loss: 0.499972 * Train accuracy / confusion: 80.00% / [[267, 91], [69, 373]], * Val accuracy / confusion: 70.19% / [[132, 98], [57, 233]] ------------------------------ Epoch 453 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.499448 - Iter 024 / 025, Loss: 0.353731 * Train accuracy / confusion: 80.25% / [[265, 90], [68, 377]], * Val accuracy / confusion: 71.73% / [[139, 91], [56, 234]] ------------------------------ Epoch 454 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.389100 - Iter 024 / 025, Loss: 0.479405 * Train accuracy / confusion: 78.62% / [[255, 101], [70, 374]], * Val accuracy / confusion: 68.27% / [[131, 99], [66, 224]] ------------------------------ Epoch 455 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.489533 - Iter 024 / 025, Loss: 0.470861 * Train accuracy / confusion: 80.62% / [[276, 83], [72, 369]], * Val accuracy / confusion: 71.15% / [[145, 85], [65, 225]] ------------------------------ Epoch 456 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.456652 - Iter 024 / 025, Loss: 0.385481 * Train accuracy / confusion: 80.62% / [[264, 95], [60, 381]], * Val accuracy / confusion: 71.15% / [[129, 101], [49, 241]] ------------------------------ Epoch 457 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.345603 - Iter 024 / 025, Loss: 0.373671 * Train accuracy / confusion: 80.00% / [[274, 90], [70, 366]], * Val accuracy / confusion: 70.00% / [[136, 94], [62, 228]] ------------------------------ Epoch 458 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.346006 - Iter 024 / 025, Loss: 0.429828 * Train accuracy / confusion: 80.62% / [[266, 88], [67, 379]], * Val accuracy / confusion: 72.31% / [[137, 93], [51, 239]] ------------------------------ Epoch 459 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.375925 - Iter 024 / 025, Loss: 0.346118 * Train accuracy / confusion: 79.62% / [[271, 88], [75, 366]], * Val accuracy / confusion: 68.85% / [[131, 99], [63, 227]] ------------------------------ Epoch 460 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.384937 - Iter 024 / 025, Loss: 0.642055 * Train accuracy / confusion: 78.12% / [[264, 92], [83, 361]], * Val accuracy / confusion: 70.77% / [[133, 97], [55, 235]] ------------------------------ Epoch 461 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.522344 - Iter 024 / 025, Loss: 0.395455 * Train accuracy / confusion: 81.25% / [[274, 87], [63, 376]], * Val accuracy / confusion: 71.54% / [[140, 90], [58, 232]] ------------------------------ Epoch 462 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.517969 - Iter 024 / 025, Loss: 0.287460 * Train accuracy / confusion: 79.62% / [[263, 90], [73, 374]], * Val accuracy / confusion: 70.19% / [[141, 89], [66, 224]] ------------------------------ Epoch 463 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.458650 - Iter 024 / 025, Loss: 0.511524 * Train accuracy / confusion: 79.88% / [[269, 89], [72, 370]], * Val accuracy / confusion: 71.73% / [[137, 93], [54, 236]] ------------------------------ Epoch 464 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.362912 - Iter 024 / 025, Loss: 0.589017 * Train accuracy / confusion: 80.12% / [[262, 90], [69, 379]], * Val accuracy / confusion: 69.62% / [[128, 102], [56, 234]] ------------------------------ Epoch 465 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.452971 - Iter 024 / 025, Loss: 0.429628 * Train accuracy / confusion: 80.50% / [[266, 88], [68, 378]], * Val accuracy / confusion: 70.77% / [[132, 98], [54, 236]] ------------------------------ Epoch 466 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.513332 - Iter 024 / 025, Loss: 0.412874 * Train accuracy / confusion: 78.62% / [[258, 98], [73, 371]], * Val accuracy / confusion: 67.50% / [[127, 103], [66, 224]] ------------------------------ Epoch 467 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.336101 - Iter 024 / 025, Loss: 0.428510 * Train accuracy / confusion: 79.00% / [[261, 95], [73, 371]], * Val accuracy / confusion: 69.23% / [[126, 104], [56, 234]] ------------------------------ Epoch 468 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.519829 - Iter 024 / 025, Loss: 0.435587 * Train accuracy / confusion: 82.12% / [[280, 73], [70, 377]], * Val accuracy / confusion: 70.58% / [[138, 92], [61, 229]] ------------------------------ Epoch 469 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.409041 - Iter 024 / 025, Loss: 0.508579 * Train accuracy / confusion: 81.12% / [[269, 88], [63, 380]], * Val accuracy / confusion: 70.77% / [[136, 94], [58, 232]] ------------------------------ Epoch 470 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.389930 - Iter 024 / 025, Loss: 0.470782 * Train accuracy / confusion: 80.62% / [[275, 83], [72, 370]], * Val accuracy / confusion: 70.38% / [[134, 96], [58, 232]] ------------------------------ Epoch 471 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.483287 - Iter 024 / 025, Loss: 0.387128 * Train accuracy / confusion: 79.50% / [[260, 92], [72, 376]], * Val accuracy / confusion: 70.00% / [[129, 101], [55, 235]] ------------------------------ Epoch 472 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.395272 - Iter 024 / 025, Loss: 0.441004 * Train accuracy / confusion: 79.00% / [[262, 92], [76, 370]], * Val accuracy / confusion: 70.96% / [[135, 95], [56, 234]] ------------------------------ Epoch 473 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.435371 - Iter 024 / 025, Loss: 0.444135 * Train accuracy / confusion: 79.88% / [[264, 90], [71, 375]], * Val accuracy / confusion: 71.35% / [[138, 92], [57, 233]] ------------------------------ Epoch 474 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.342347 - Iter 024 / 025, Loss: 0.400484 * Train accuracy / confusion: 79.88% / [[263, 93], [68, 376]], * Val accuracy / confusion: 70.77% / [[138, 92], [60, 230]] ------------------------------ Epoch 475 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.431822 - Iter 024 / 025, Loss: 0.585781 * Train accuracy / confusion: 80.75% / [[263, 92], [62, 383]], * Val accuracy / confusion: 70.77% / [[133, 97], [55, 235]] ------------------------------ Epoch 476 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.377401 - Iter 024 / 025, Loss: 0.391421 * Train accuracy / confusion: 79.88% / [[269, 87], [74, 370]], * Val accuracy / confusion: 70.00% / [[129, 101], [55, 235]] ------------------------------ Epoch 477 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.316046 - Iter 024 / 025, Loss: 0.352171 * Train accuracy / confusion: 80.88% / [[275, 85], [68, 372]], * Val accuracy / confusion: 71.73% / [[135, 95], [52, 238]] ------------------------------ Epoch 478 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.410609 - Iter 024 / 025, Loss: 0.466259 * Train accuracy / confusion: 80.88% / [[274, 84], [69, 373]], * Val accuracy / confusion: 71.73% / [[139, 91], [56, 234]] ------------------------------ Epoch 479 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.391831 - Iter 024 / 025, Loss: 0.426327 * Train accuracy / confusion: 77.50% / [[258, 102], [78, 362]], * Val accuracy / confusion: 71.92% / [[138, 92], [54, 236]] ------------------------------ Epoch 480 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.548846 - Iter 024 / 025, Loss: 0.449396 * Train accuracy / confusion: 79.38% / [[266, 91], [74, 369]], * Val accuracy / confusion: 71.35% / [[144, 86], [63, 227]] ------------------------------ Epoch 481 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.410411 - Iter 024 / 025, Loss: 0.547418 * Train accuracy / confusion: 79.75% / [[267, 93], [69, 371]], * Val accuracy / confusion: 72.88% / [[149, 81], [60, 230]] ------------------------------ Epoch 482 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.404756 - Iter 024 / 025, Loss: 0.428248 * Train accuracy / confusion: 80.25% / [[260, 92], [66, 382]], * Val accuracy / confusion: 69.04% / [[134, 96], [65, 225]] ------------------------------ Epoch 483 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.480722 - Iter 024 / 025, Loss: 0.472890 * Train accuracy / confusion: 78.38% / [[269, 88], [85, 358]], * Val accuracy / confusion: 70.00% / [[122, 108], [48, 242]] ------------------------------ Epoch 484 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.569306 - Iter 024 / 025, Loss: 0.520283 * Train accuracy / confusion: 80.25% / [[267, 88], [70, 375]], * Val accuracy / confusion: 70.77% / [[127, 103], [49, 241]] ------------------------------ Epoch 485 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.384667 - Iter 024 / 025, Loss: 0.373501 * Train accuracy / confusion: 81.00% / [[270, 90], [62, 378]], * Val accuracy / confusion: 71.35% / [[134, 96], [53, 237]] ------------------------------ Epoch 486 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.444006 - Iter 024 / 025, Loss: 0.294433 * Train accuracy / confusion: 78.50% / [[265, 94], [78, 363]], * Val accuracy / confusion: 70.00% / [[135, 95], [61, 229]] ------------------------------ Epoch 487 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.282487 - Iter 024 / 025, Loss: 0.405771 * Train accuracy / confusion: 83.00% / [[281, 76], [60, 383]], * Val accuracy / confusion: 72.12% / [[142, 88], [57, 233]] ------------------------------ Epoch 488 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.343744 - Iter 024 / 025, Loss: 0.455833 * Train accuracy / confusion: 79.38% / [[258, 91], [74, 377]], * Val accuracy / confusion: 68.65% / [[130, 100], [63, 227]] ------------------------------ Epoch 489 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.482667 - Iter 024 / 025, Loss: 0.421727 * Train accuracy / confusion: 80.62% / [[269, 86], [69, 376]], * Val accuracy / confusion: 69.23% / [[135, 95], [65, 225]] ------------------------------ Epoch 490 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.415491 - Iter 024 / 025, Loss: 0.409043 * Train accuracy / confusion: 79.62% / [[264, 88], [75, 373]], * Val accuracy / confusion: 69.62% / [[123, 107], [51, 239]] ------------------------------ Epoch 491 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.365375 - Iter 024 / 025, Loss: 0.497588 * Train accuracy / confusion: 79.88% / [[264, 93], [68, 375]], * Val accuracy / confusion: 68.46% / [[131, 99], [65, 225]] ------------------------------ Epoch 492 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.347057 - Iter 024 / 025, Loss: 0.381843 * Train accuracy / confusion: 81.12% / [[271, 85], [66, 378]], * Val accuracy / confusion: 72.88% / [[145, 85], [56, 234]] ------------------------------ Epoch 493 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.600828 - Iter 024 / 025, Loss: 0.439320 * Train accuracy / confusion: 80.38% / [[266, 91], [66, 377]], * Val accuracy / confusion: 70.38% / [[139, 91], [63, 227]] ------------------------------ Epoch 494 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.352045 - Iter 024 / 025, Loss: 0.476777 * Train accuracy / confusion: 79.75% / [[267, 89], [73, 371]], * Val accuracy / confusion: 70.19% / [[140, 90], [65, 225]] ------------------------------ Epoch 495 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.390466 - Iter 024 / 025, Loss: 0.511526 * Train accuracy / confusion: 79.50% / [[265, 94], [70, 371]], * Val accuracy / confusion: 68.46% / [[122, 108], [56, 234]] ------------------------------ Epoch 496 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.463271 - Iter 024 / 025, Loss: 0.364198 * Train accuracy / confusion: 78.12% / [[253, 98], [77, 372]], * Val accuracy / confusion: 70.00% / [[133, 97], [59, 231]] ------------------------------ Epoch 497 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.648927 - Iter 024 / 025, Loss: 0.496330 * Train accuracy / confusion: 77.62% / [[256, 99], [80, 365]], * Val accuracy / confusion: 67.12% / [[114, 116], [55, 235]] ------------------------------ Epoch 498 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.494126 - Iter 024 / 025, Loss: 0.500781 * Train accuracy / confusion: 79.25% / [[260, 94], [72, 374]], * Val accuracy / confusion: 72.31% / [[137, 93], [51, 239]] ------------------------------ Epoch 499 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.380157 - Iter 024 / 025, Loss: 0.383427 * Train accuracy / confusion: 78.38% / [[263, 97], [76, 364]], * Val accuracy / confusion: 71.35% / [[133, 97], [52, 238]] ------------------------------ Epoch 500 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.526194 - Iter 024 / 025, Loss: 0.415835 * Train accuracy / confusion: 80.25% / [[268, 82], [76, 374]], * Val accuracy / confusion: 68.85% / [[128, 102], [60, 230]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 72.92% - Confusion matrix (last model): [[ 938 472] [ 373 1337]]
- Test accuracy (best model): 69.94% - Confusion matrix (best model): [[1015 395] [ 543 1167]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_ResNet_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '00299': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '00671212_160819'},
'00854': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01138301_230114'},
'01026': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01225123_050815'},
'00176': {'GT': 0, 'Acc': ' 70.00%', 'Pred': [21, 9], 'edfname': '00602435_270217'},
'00591': {'GT': 0, 'Acc': ' 83.33%', 'Pred': [25, 5], 'edfname': '00896386_240914'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00811': {'GT': 1, 'Acc': ' 10.00%', 'Pred': [27, 3], 'edfname': '01116389_271118'},
'01235': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01336270_040717'},
'00835': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01134450_140519'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'00719': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01006707_260319'},
'00495': {'GT': 1, 'Acc': ' 70.00%', 'Pred': [9, 21], 'edfname': '00805584_090819'},
'00862': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139924_300315'},
'00913': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '01151967_160414'},
'00097': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00372136_181214'},
'00122': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00416942_190516'},
'00439': {'GT': 0, 'Acc': ' 73.33%', 'Pred': [22, 8], 'edfname': '00760780_141118'},
'01378': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01432133_160519'},
'00705': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_270116'},
'00212': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00617893_231018'},
'01105': {'GT': 0, 'Acc': ' 60.00%', 'Pred': [18, 12], 'edfname': '01266696_110516'},
'00671': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00958455_200917'},
'00531': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00840844_250119'},
'00192': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00608961_131118'},
'00643': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00948785_120116'},
'01177': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '01300390_251116'},
'01209': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01318352_281118'},
'00341': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695058_191017'},
'00357': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00707209_261219'},
'00527': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00840062_080519'},
'01307': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01376302_060718'},
'00058': {'GT': 0, 'Acc': ' 40.00%', 'Pred': [12, 18], 'edfname': '00285244_020414'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00508': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00817022_010415'},
'00021': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00141670_081217'},
'00408': {'GT': 0, 'Acc': ' 13.33%', 'Pred': [4, 26], 'edfname': '00740750_110315'},
'00385': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00723232_270318'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'01330': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01392885_240718'},
'00329': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '00685248_150414'},
'00277': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00657017_281218'},
'00900': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01147100'},
'00700': {'GT': 1, 'Acc': ' 36.67%', 'Pred': [19, 11], 'edfname': '00985401_011117'},
'00584': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '00891889_060717'},
'01066': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01242983_071215'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': ' 76.67%', 'Pred': [23, 7], 'edfname': '00369252_131216'},
'01165': {'GT': 0, 'Acc': ' 53.33%', 'Pred': [16, 14], 'edfname': '01296533_281116'},
'00697': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00983533_290618'},
'00030': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_230317'},
'01123': {'GT': 1, 'Acc': ' 10.00%', 'Pred': [27, 3], 'edfname': '01276165_040117'},
'00982': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01200248_290120'},
'00917': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01154159_230414'},
'00255': {'GT': 1, 'Acc': ' 23.33%', 'Pred': [23, 7], 'edfname': '00645911_021115'},
'01039': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01235034_290120'},
'00961': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01182545_070316'},
'00338': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00692685_200919'},
'00346': {'GT': 1, 'Acc': ' 40.00%', 'Pred': [18, 12], 'edfname': '00698358_020916'},
'00793': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01086373_020615'},
'00704': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_240215'},
'00125': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00418981_090316'},
'00859': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139924_060417'},
'00471': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00784417_100315'},
'00498': {'GT': 1, 'Acc': ' 10.00%', 'Pred': [27, 3], 'edfname': '00809366_050116'},
'01239': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01338557_190717'},
'00481': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00796686_020819'},
'00369': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00715828_111016'},
'01281': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01358607_280918'},
'01360': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01415643_150119'},
'01288': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01364379_260919'},
'00885': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '01142810_180214'},
'00858': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01139894_140214'},
'01138': {'GT': 0, 'Acc': ' 46.67%', 'Pred': [14, 16], 'edfname': '01281605_070716'},
'00821': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '01128393_300715'},
'00870': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01139947_120214'},
'01215': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01321744_130417'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00464': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00779318_101117'},
'00923': {'GT': 0, 'Acc': ' 66.67%', 'Pred': [20, 10], 'edfname': '01155730_070514'},
'00815': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01125477_030918'},
'01287': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01364379_230118'},
'01160': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01295899_041016'},
'00104': {'GT': 1, 'Acc': ' 16.67%', 'Pred': [25, 5], 'edfname': '00395714_170915'},
'01353': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '01410438_241218'},
'01267': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01351393_111119'},
'01156': {'GT': 1, 'Acc': ' 50.00%', 'Pred': [15, 15], 'edfname': '01293646_120719'},
'00504': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '00813343_041218'},
'01045': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01235281_191015'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00094': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00366974_061118'},
'00741': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '01025734_280715'},
'00303': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '00672867_031116'},
'00156': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00502785_041019'},
'00851': {'GT': 0, 'Acc': ' 43.33%', 'Pred': [13, 17], 'edfname': '01138297_230114'},
'00730': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01011922_270815'},
'00343': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '00695272_100519'},
'00756': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01035162_180119'},
'01232': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01335435_121119'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01339759_310717'},
'00588': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00895530_090616'},
'00076': {'GT': 1, 'Acc': ' 26.67%', 'Pred': [22, 8], 'edfname': '00317645_311016'},
'00653': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00952170_060516'}}
model = ResNet(block=BasicResBlock, conv_layers=[1, 1, 1, 1], n_fc=3,
n_input=train_dataset[0]['signal'].shape[0], n_output=2, n_start=64,
kernel_size=9, use_age=False)
model = model.to(device, dtype=torch.float32)
print(model)
print()
n = count_parameters(model)
print(f'The Number of parameters of the model: {n:,}')
ResNet(
(input_stage): Sequential(
(0): Conv1d(20, 64, kernel_size=(27,), stride=(2,), padding=(13,), bias=False)
(1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU()
)
(conv_stage1): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(64, 64, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage2): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(64, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(128, 128, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(64, 128, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage3): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(128, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(256, 256, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(128, 256, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(conv_stage4): Sequential(
(0): BasicResBlock(
(conv1): Conv1d(256, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv1d(512, 512, kernel_size=(9,), stride=(1,), padding=(4,), bias=False)
(bn2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
(1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)
)
(final_pool): AdaptiveAvgPool1d(output_size=1)
(fc_stage): Sequential(
(0): Sequential(
(0): Linear(in_features=512, out_features=256, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(1): Sequential(
(0): Linear(in_features=256, out_features=128, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(2): Sequential(
(0): Linear(in_features=128, out_features=64, bias=False)
(1): Dropout(p=0.1, inplace=False)
(2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU()
)
(3): Linear(in_features=64, out_features=2, bias=True)
)
)
The Number of parameters of the model: 5,104,002
record = learning_rate_search(model,
min_log_lr=-4.5,
max_log_lr=-1.4,
trials=300,
epochs=1)
draw_learning_rate_record(record)
best_log_lr = record[np.argmax(np.array([v for lr, v in record]))][0]
best_log_lr = -3.0
print('best_log_lr:', best_log_lr)
best_log_lr: -3.0
# reduce the learning after [lr_schedule_step] epochs by a factor of 10
n_epoch = 500
lr_schedule_step = 200
log_interval = len(train_loader) // 2
loss_history = []
train_acc_history = []
val_acc_history = []
best_val_acc = 0
model.reset_weights()
optimizer = optim.AdamW(model.parameters(), lr=10 ** best_log_lr, weight_decay=0.0001)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=lr_schedule_step, gamma=0.1)
print(f'{"*"*40} Training Starts {"*"*40}')
for epoch in tqdm(range(1, n_epoch + 1)):
print(f'{"-"*30} Epoch {epoch:03d} / {n_epoch:03d}, Learning rate: {optimizer.param_groups[-1]["lr"]:.2e} {"-"*30}')
# train
loss, train_accuracy, train_confusion = train_one_epoch(model, optimizer, log_interval)
loss_history.extend(loss)
train_acc_history.append(train_accuracy)
# validation
val_accuracy, val_confusion = check_val_accuracy(model, repeat=5)
val_acc_history.append(val_accuracy)
if best_val_acc < val_accuracy:
best_val_acc = val_accuracy
best_model_state = deepcopy(model.state_dict())
# learning rate schedule
scheduler.step()
print()
print(f'* Train accuracy / confusion: {train_accuracy:.2f}% / {train_confusion.tolist()}, ')
print(f'* Val accuracy / confusion: {val_accuracy:.2f}% / {val_confusion.tolist()}')
print()
print(f'{"*"*40} Training Ends {"*"*40}')
# draw the training loss plot
draw_loss_plot(loss_history)
draw_accuracy_history(train_acc_history, val_acc_history)
# test the last model
last_model_state = deepcopy(model.state_dict())
last_test_accuracy, last_test_confusion, last_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (last model): {last_test_accuracy:.2f}%')
print('- Confusion matrix (last model):\n', last_test_confusion)
print()
draw_confusion(last_test_confusion)
# test the best model
model.load_state_dict(best_model_state)
best_test_accuracy, best_test_confusion, best_test_debug = check_test_accuracy(model, repeat=30)
print(f'- Test accuracy (best model): {best_test_accuracy:.2f}%')
print('- Confusion matrix (best model):\n', best_test_confusion)
print()
draw_confusion(best_test_confusion)
**************************************** Training Starts ****************************************
------------------------------ Epoch 001 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.674103 - Iter 024 / 025, Loss: 0.718975 * Train accuracy / confusion: 50.62% / [[186, 169], [226, 219]], * Val accuracy / confusion: 44.81% / [[227, 3], [284, 6]] ------------------------------ Epoch 002 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.650572 - Iter 024 / 025, Loss: 0.676701 * Train accuracy / confusion: 56.38% / [[102, 255], [94, 349]], * Val accuracy / confusion: 58.46% / [[31, 199], [17, 273]] ------------------------------ Epoch 003 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.620160 - Iter 024 / 025, Loss: 0.580529 * Train accuracy / confusion: 61.00% / [[137, 216], [96, 351]], * Val accuracy / confusion: 61.15% / [[167, 63], [139, 151]] ------------------------------ Epoch 004 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.733975 - Iter 024 / 025, Loss: 0.713182 * Train accuracy / confusion: 61.00% / [[167, 195], [117, 321]], * Val accuracy / confusion: 60.58% / [[36, 194], [11, 279]] ------------------------------ Epoch 005 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.689611 - Iter 024 / 025, Loss: 0.592458 * Train accuracy / confusion: 62.62% / [[186, 170], [129, 315]], * Val accuracy / confusion: 62.69% / [[156, 74], [120, 170]] ------------------------------ Epoch 006 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.589632 - Iter 024 / 025, Loss: 0.506905 * Train accuracy / confusion: 63.62% / [[189, 167], [124, 320]], * Val accuracy / confusion: 65.00% / [[89, 141], [41, 249]] ------------------------------ Epoch 007 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.618460 - Iter 024 / 025, Loss: 0.580094 * Train accuracy / confusion: 62.12% / [[166, 193], [110, 331]], * Val accuracy / confusion: 66.92% / [[142, 88], [84, 206]] ------------------------------ Epoch 008 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.631465 - Iter 024 / 025, Loss: 0.589839 * Train accuracy / confusion: 64.00% / [[183, 174], [114, 329]], * Val accuracy / confusion: 64.62% / [[69, 161], [23, 267]] ------------------------------ Epoch 009 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.575197 - Iter 024 / 025, Loss: 0.521615 * Train accuracy / confusion: 65.75% / [[194, 165], [109, 332]], * Val accuracy / confusion: 62.69% / [[49, 181], [13, 277]] ------------------------------ Epoch 010 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.594377 - Iter 024 / 025, Loss: 0.475759 * Train accuracy / confusion: 68.12% / [[216, 143], [112, 329]], * Val accuracy / confusion: 60.96% / [[223, 7], [196, 94]] ------------------------------ Epoch 011 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.556694 - Iter 024 / 025, Loss: 0.631981 * Train accuracy / confusion: 65.88% / [[193, 162], [111, 334]], * Val accuracy / confusion: 68.46% / [[113, 117], [47, 243]] ------------------------------ Epoch 012 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.628179 - Iter 024 / 025, Loss: 0.692405 * Train accuracy / confusion: 66.62% / [[206, 150], [117, 327]], * Val accuracy / confusion: 63.08% / [[60, 170], [22, 268]] ------------------------------ Epoch 013 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.577178 - Iter 024 / 025, Loss: 0.639385 * Train accuracy / confusion: 67.88% / [[230, 129], [128, 313]], * Val accuracy / confusion: 59.04% / [[19, 211], [2, 288]] ------------------------------ Epoch 014 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.416803 - Iter 024 / 025, Loss: 0.532040 * Train accuracy / confusion: 66.88% / [[222, 136], [129, 313]], * Val accuracy / confusion: 65.96% / [[182, 48], [129, 161]] ------------------------------ Epoch 015 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.461556 - Iter 024 / 025, Loss: 0.616668 * Train accuracy / confusion: 68.38% / [[238, 120], [133, 309]], * Val accuracy / confusion: 66.54% / [[110, 120], [54, 236]] ------------------------------ Epoch 016 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.686105 - Iter 024 / 025, Loss: 0.594239 * Train accuracy / confusion: 68.38% / [[207, 149], [104, 340]], * Val accuracy / confusion: 66.15% / [[107, 123], [53, 237]] ------------------------------ Epoch 017 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.538033 - Iter 024 / 025, Loss: 0.514059 * Train accuracy / confusion: 70.00% / [[217, 139], [101, 343]], * Val accuracy / confusion: 67.12% / [[131, 99], [72, 218]] ------------------------------ Epoch 018 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.619603 - Iter 024 / 025, Loss: 0.586699 * Train accuracy / confusion: 69.50% / [[209, 140], [104, 347]], * Val accuracy / confusion: 68.46% / [[146, 84], [80, 210]] ------------------------------ Epoch 019 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.615374 - Iter 024 / 025, Loss: 0.465746 * Train accuracy / confusion: 70.88% / [[227, 131], [102, 340]], * Val accuracy / confusion: 60.96% / [[39, 191], [12, 278]] ------------------------------ Epoch 020 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.520283 - Iter 024 / 025, Loss: 0.617440 * Train accuracy / confusion: 69.88% / [[241, 111], [130, 318]], * Val accuracy / confusion: 69.42% / [[149, 81], [78, 212]] ------------------------------ Epoch 021 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.505435 - Iter 024 / 025, Loss: 0.446800 * Train accuracy / confusion: 70.00% / [[219, 136], [104, 341]], * Val accuracy / confusion: 63.08% / [[48, 182], [10, 280]] ------------------------------ Epoch 022 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.648800 - Iter 024 / 025, Loss: 0.685134 * Train accuracy / confusion: 70.75% / [[246, 113], [121, 320]], * Val accuracy / confusion: 67.31% / [[105, 125], [45, 245]] ------------------------------ Epoch 023 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.480192 - Iter 024 / 025, Loss: 0.689598 * Train accuracy / confusion: 71.25% / [[240, 115], [115, 330]], * Val accuracy / confusion: 68.46% / [[164, 66], [98, 192]] ------------------------------ Epoch 024 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.594651 - Iter 024 / 025, Loss: 0.510869 * Train accuracy / confusion: 69.62% / [[253, 106], [137, 304]], * Val accuracy / confusion: 62.69% / [[203, 27], [167, 123]] ------------------------------ Epoch 025 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.505020 - Iter 024 / 025, Loss: 0.597271 * Train accuracy / confusion: 70.12% / [[241, 119], [120, 320]], * Val accuracy / confusion: 63.08% / [[103, 127], [65, 225]] ------------------------------ Epoch 026 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.649824 - Iter 024 / 025, Loss: 0.537723 * Train accuracy / confusion: 72.38% / [[243, 110], [111, 336]], * Val accuracy / confusion: 67.12% / [[99, 131], [40, 250]] ------------------------------ Epoch 027 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.544313 - Iter 024 / 025, Loss: 0.632655 * Train accuracy / confusion: 70.88% / [[247, 112], [121, 320]], * Val accuracy / confusion: 62.50% / [[190, 40], [155, 135]] ------------------------------ Epoch 028 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.496444 - Iter 024 / 025, Loss: 0.559496 * Train accuracy / confusion: 69.88% / [[225, 130], [111, 334]], * Val accuracy / confusion: 69.23% / [[122, 108], [52, 238]] ------------------------------ Epoch 029 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.591341 - Iter 024 / 025, Loss: 0.469074 * Train accuracy / confusion: 71.12% / [[227, 132], [99, 342]], * Val accuracy / confusion: 65.19% / [[60, 170], [11, 279]] ------------------------------ Epoch 030 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.518409 - Iter 024 / 025, Loss: 0.562120 * Train accuracy / confusion: 74.50% / [[242, 117], [87, 354]], * Val accuracy / confusion: 71.92% / [[126, 104], [42, 248]] ------------------------------ Epoch 031 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.452130 - Iter 024 / 025, Loss: 0.511161 * Train accuracy / confusion: 72.12% / [[244, 116], [107, 333]], * Val accuracy / confusion: 66.15% / [[100, 130], [46, 244]] ------------------------------ Epoch 032 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488929 - Iter 024 / 025, Loss: 0.594706 * Train accuracy / confusion: 73.75% / [[245, 108], [102, 345]], * Val accuracy / confusion: 62.31% / [[140, 90], [106, 184]] ------------------------------ Epoch 033 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.487651 - Iter 024 / 025, Loss: 0.620754 * Train accuracy / confusion: 69.25% / [[224, 130], [116, 330]], * Val accuracy / confusion: 68.27% / [[187, 43], [122, 168]] ------------------------------ Epoch 034 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.517088 - Iter 024 / 025, Loss: 0.529764 * Train accuracy / confusion: 71.88% / [[246, 109], [116, 329]], * Val accuracy / confusion: 70.58% / [[157, 73], [80, 210]] ------------------------------ Epoch 035 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.628673 - Iter 024 / 025, Loss: 0.440858 * Train accuracy / confusion: 70.62% / [[242, 115], [120, 323]], * Val accuracy / confusion: 71.15% / [[153, 77], [73, 217]] ------------------------------ Epoch 036 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.546327 - Iter 024 / 025, Loss: 0.595125 * Train accuracy / confusion: 71.62% / [[248, 105], [122, 325]], * Val accuracy / confusion: 68.85% / [[114, 116], [46, 244]] ------------------------------ Epoch 037 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477705 - Iter 024 / 025, Loss: 0.556602 * Train accuracy / confusion: 71.25% / [[245, 109], [121, 325]], * Val accuracy / confusion: 70.96% / [[142, 88], [63, 227]] ------------------------------ Epoch 038 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488544 - Iter 024 / 025, Loss: 0.900807 * Train accuracy / confusion: 72.00% / [[238, 123], [101, 338]], * Val accuracy / confusion: 60.96% / [[209, 21], [182, 108]] ------------------------------ Epoch 039 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.700461 - Iter 024 / 025, Loss: 0.599477 * Train accuracy / confusion: 72.00% / [[240, 113], [111, 336]], * Val accuracy / confusion: 69.42% / [[137, 93], [66, 224]] ------------------------------ Epoch 040 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.567964 - Iter 024 / 025, Loss: 0.628876 * Train accuracy / confusion: 72.88% / [[240, 112], [105, 343]], * Val accuracy / confusion: 59.04% / [[25, 205], [8, 282]] ------------------------------ Epoch 041 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.552678 - Iter 024 / 025, Loss: 0.503638 * Train accuracy / confusion: 73.00% / [[249, 107], [109, 335]], * Val accuracy / confusion: 63.65% / [[65, 165], [24, 266]] ------------------------------ Epoch 042 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547349 - Iter 024 / 025, Loss: 0.537397 * Train accuracy / confusion: 71.12% / [[226, 131], [100, 343]], * Val accuracy / confusion: 64.23% / [[93, 137], [49, 241]] ------------------------------ Epoch 043 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.646306 - Iter 024 / 025, Loss: 0.581849 * Train accuracy / confusion: 75.12% / [[252, 109], [90, 349]], * Val accuracy / confusion: 70.58% / [[130, 100], [53, 237]] ------------------------------ Epoch 044 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.671067 - Iter 024 / 025, Loss: 0.548035 * Train accuracy / confusion: 72.75% / [[248, 112], [106, 334]], * Val accuracy / confusion: 67.69% / [[127, 103], [65, 225]] ------------------------------ Epoch 045 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473574 - Iter 024 / 025, Loss: 0.533524 * Train accuracy / confusion: 71.88% / [[255, 103], [122, 320]], * Val accuracy / confusion: 70.38% / [[120, 110], [44, 246]] ------------------------------ Epoch 046 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.466501 - Iter 024 / 025, Loss: 0.501096 * Train accuracy / confusion: 72.62% / [[227, 128], [91, 354]], * Val accuracy / confusion: 66.35% / [[75, 155], [20, 270]] ------------------------------ Epoch 047 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.716260 - Iter 024 / 025, Loss: 0.660505 * Train accuracy / confusion: 73.75% / [[241, 118], [92, 349]], * Val accuracy / confusion: 68.27% / [[118, 112], [53, 237]] ------------------------------ Epoch 048 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.403519 - Iter 024 / 025, Loss: 0.700345 * Train accuracy / confusion: 71.00% / [[238, 123], [109, 330]], * Val accuracy / confusion: 69.42% / [[147, 83], [76, 214]] ------------------------------ Epoch 049 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.482240 - Iter 024 / 025, Loss: 0.588716 * Train accuracy / confusion: 71.38% / [[236, 119], [110, 335]], * Val accuracy / confusion: 67.88% / [[117, 113], [54, 236]] ------------------------------ Epoch 050 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.557179 - Iter 024 / 025, Loss: 0.523953 * Train accuracy / confusion: 72.38% / [[233, 118], [103, 346]], * Val accuracy / confusion: 71.54% / [[164, 66], [82, 208]] ------------------------------ Epoch 051 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.480092 - Iter 024 / 025, Loss: 0.610138 * Train accuracy / confusion: 73.38% / [[250, 109], [104, 337]], * Val accuracy / confusion: 70.77% / [[141, 89], [63, 227]] ------------------------------ Epoch 052 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547917 - Iter 024 / 025, Loss: 0.472618 * Train accuracy / confusion: 73.12% / [[231, 122], [93, 354]], * Val accuracy / confusion: 66.54% / [[196, 34], [140, 150]] ------------------------------ Epoch 053 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.455555 - Iter 024 / 025, Loss: 0.433245 * Train accuracy / confusion: 73.75% / [[250, 109], [101, 340]], * Val accuracy / confusion: 64.23% / [[75, 155], [31, 259]] ------------------------------ Epoch 054 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.384899 - Iter 024 / 025, Loss: 0.552345 * Train accuracy / confusion: 73.25% / [[251, 107], [107, 335]], * Val accuracy / confusion: 66.73% / [[105, 125], [48, 242]] ------------------------------ Epoch 055 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.672535 - Iter 024 / 025, Loss: 0.547072 * Train accuracy / confusion: 72.75% / [[246, 105], [113, 336]], * Val accuracy / confusion: 69.04% / [[154, 76], [85, 205]] ------------------------------ Epoch 056 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.559022 - Iter 024 / 025, Loss: 0.411601 * Train accuracy / confusion: 73.50% / [[257, 95], [117, 331]], * Val accuracy / confusion: 66.15% / [[153, 77], [99, 191]] ------------------------------ Epoch 057 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.481499 - Iter 024 / 025, Loss: 0.597547 * Train accuracy / confusion: 74.00% / [[247, 111], [97, 345]], * Val accuracy / confusion: 68.27% / [[139, 91], [74, 216]] ------------------------------ Epoch 058 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.484458 - Iter 024 / 025, Loss: 0.538770 * Train accuracy / confusion: 71.75% / [[257, 99], [127, 317]], * Val accuracy / confusion: 69.42% / [[105, 125], [34, 256]] ------------------------------ Epoch 059 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.667446 - Iter 024 / 025, Loss: 0.454023 * Train accuracy / confusion: 71.50% / [[248, 105], [123, 324]], * Val accuracy / confusion: 68.27% / [[158, 72], [93, 197]] ------------------------------ Epoch 060 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.609462 - Iter 024 / 025, Loss: 0.663004 * Train accuracy / confusion: 75.12% / [[249, 105], [94, 352]], * Val accuracy / confusion: 69.62% / [[180, 50], [108, 182]] ------------------------------ Epoch 061 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.532095 - Iter 024 / 025, Loss: 0.661200 * Train accuracy / confusion: 72.38% / [[228, 131], [90, 351]], * Val accuracy / confusion: 64.42% / [[59, 171], [14, 276]] ------------------------------ Epoch 062 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.656082 - Iter 024 / 025, Loss: 0.479564 * Train accuracy / confusion: 75.00% / [[263, 94], [106, 337]], * Val accuracy / confusion: 66.54% / [[91, 139], [35, 255]] ------------------------------ Epoch 063 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.652802 - Iter 024 / 025, Loss: 0.717260 * Train accuracy / confusion: 71.38% / [[222, 134], [95, 349]], * Val accuracy / confusion: 68.27% / [[169, 61], [104, 186]] ------------------------------ Epoch 064 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.738235 - Iter 024 / 025, Loss: 0.535931 * Train accuracy / confusion: 73.88% / [[248, 109], [100, 343]], * Val accuracy / confusion: 69.23% / [[123, 107], [53, 237]] ------------------------------ Epoch 065 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.619093 - Iter 024 / 025, Loss: 0.587244 * Train accuracy / confusion: 74.50% / [[239, 116], [88, 357]], * Val accuracy / confusion: 69.04% / [[190, 40], [121, 169]] ------------------------------ Epoch 066 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.584262 - Iter 024 / 025, Loss: 0.538065 * Train accuracy / confusion: 74.62% / [[247, 104], [99, 350]], * Val accuracy / confusion: 66.35% / [[155, 75], [100, 190]] ------------------------------ Epoch 067 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.557341 - Iter 024 / 025, Loss: 0.342308 * Train accuracy / confusion: 73.38% / [[245, 114], [99, 342]], * Val accuracy / confusion: 64.23% / [[84, 146], [40, 250]] ------------------------------ Epoch 068 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.460942 - Iter 024 / 025, Loss: 0.572806 * Train accuracy / confusion: 73.50% / [[241, 115], [97, 347]], * Val accuracy / confusion: 68.85% / [[136, 94], [68, 222]] ------------------------------ Epoch 069 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.404300 - Iter 024 / 025, Loss: 0.538524 * Train accuracy / confusion: 72.50% / [[239, 113], [107, 341]], * Val accuracy / confusion: 62.69% / [[203, 27], [167, 123]] ------------------------------ Epoch 070 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.482531 - Iter 024 / 025, Loss: 0.602395 * Train accuracy / confusion: 73.00% / [[241, 119], [97, 343]], * Val accuracy / confusion: 66.35% / [[85, 145], [30, 260]] ------------------------------ Epoch 071 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.404577 - Iter 024 / 025, Loss: 0.485991 * Train accuracy / confusion: 73.62% / [[241, 114], [97, 348]], * Val accuracy / confusion: 63.85% / [[66, 164], [24, 266]] ------------------------------ Epoch 072 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.544717 - Iter 024 / 025, Loss: 0.457740 * Train accuracy / confusion: 75.75% / [[252, 106], [88, 354]], * Val accuracy / confusion: 66.35% / [[108, 122], [53, 237]] ------------------------------ Epoch 073 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.604693 - Iter 024 / 025, Loss: 0.484815 * Train accuracy / confusion: 74.00% / [[251, 101], [107, 341]], * Val accuracy / confusion: 67.50% / [[134, 96], [73, 217]] ------------------------------ Epoch 074 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.547495 - Iter 024 / 025, Loss: 0.396233 * Train accuracy / confusion: 74.75% / [[245, 113], [89, 353]], * Val accuracy / confusion: 68.46% / [[155, 75], [89, 201]] ------------------------------ Epoch 075 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.523491 - Iter 024 / 025, Loss: 0.671563 * Train accuracy / confusion: 75.75% / [[254, 104], [90, 352]], * Val accuracy / confusion: 70.00% / [[147, 83], [73, 217]] ------------------------------ Epoch 076 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.620531 - Iter 024 / 025, Loss: 0.559785 * Train accuracy / confusion: 72.50% / [[250, 108], [112, 330]], * Val accuracy / confusion: 65.58% / [[189, 41], [138, 152]] ------------------------------ Epoch 077 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.494950 - Iter 024 / 025, Loss: 0.457382 * Train accuracy / confusion: 73.75% / [[245, 110], [100, 345]], * Val accuracy / confusion: 65.96% / [[84, 146], [31, 259]] ------------------------------ Epoch 078 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.491534 - Iter 024 / 025, Loss: 0.652217 * Train accuracy / confusion: 75.50% / [[256, 98], [98, 348]], * Val accuracy / confusion: 67.50% / [[122, 108], [61, 229]] ------------------------------ Epoch 079 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.469629 - Iter 024 / 025, Loss: 0.628382 * Train accuracy / confusion: 74.88% / [[251, 109], [92, 348]], * Val accuracy / confusion: 68.85% / [[178, 52], [110, 180]] ------------------------------ Epoch 080 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.505607 - Iter 024 / 025, Loss: 0.755819 * Train accuracy / confusion: 76.50% / [[253, 100], [88, 359]], * Val accuracy / confusion: 70.77% / [[164, 66], [86, 204]] ------------------------------ Epoch 081 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.663729 - Iter 024 / 025, Loss: 0.558360 * Train accuracy / confusion: 73.25% / [[241, 114], [100, 345]], * Val accuracy / confusion: 64.62% / [[84, 146], [38, 252]] ------------------------------ Epoch 082 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.472264 - Iter 024 / 025, Loss: 0.505541 * Train accuracy / confusion: 75.75% / [[256, 99], [95, 350]], * Val accuracy / confusion: 68.27% / [[159, 71], [94, 196]] ------------------------------ Epoch 083 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.506128 - Iter 024 / 025, Loss: 0.351842 * Train accuracy / confusion: 73.62% / [[249, 111], [100, 340]], * Val accuracy / confusion: 65.96% / [[82, 148], [29, 261]] ------------------------------ Epoch 084 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.364331 - Iter 024 / 025, Loss: 0.496574 * Train accuracy / confusion: 76.75% / [[251, 107], [79, 363]], * Val accuracy / confusion: 70.00% / [[166, 64], [92, 198]] ------------------------------ Epoch 085 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.606832 - Iter 024 / 025, Loss: 0.388673 * Train accuracy / confusion: 74.25% / [[265, 89], [117, 329]], * Val accuracy / confusion: 70.19% / [[141, 89], [66, 224]] ------------------------------ Epoch 086 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433971 - Iter 024 / 025, Loss: 0.741237 * Train accuracy / confusion: 75.00% / [[266, 91], [109, 334]], * Val accuracy / confusion: 67.88% / [[112, 118], [49, 241]] ------------------------------ Epoch 087 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.398371 - Iter 024 / 025, Loss: 0.383458 * Train accuracy / confusion: 75.38% / [[262, 94], [103, 341]], * Val accuracy / confusion: 60.58% / [[45, 185], [20, 270]] ------------------------------ Epoch 088 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.463903 - Iter 024 / 025, Loss: 0.646503 * Train accuracy / confusion: 73.88% / [[242, 118], [91, 349]], * Val accuracy / confusion: 65.38% / [[151, 79], [101, 189]] ------------------------------ Epoch 089 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.584074 - Iter 024 / 025, Loss: 0.496284 * Train accuracy / confusion: 73.38% / [[247, 108], [105, 340]], * Val accuracy / confusion: 66.92% / [[147, 83], [89, 201]] ------------------------------ Epoch 090 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.780545 - Iter 024 / 025, Loss: 0.388197 * Train accuracy / confusion: 74.38% / [[254, 105], [100, 341]], * Val accuracy / confusion: 65.58% / [[111, 119], [60, 230]] ------------------------------ Epoch 091 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.720095 - Iter 024 / 025, Loss: 0.450899 * Train accuracy / confusion: 75.25% / [[250, 108], [90, 352]], * Val accuracy / confusion: 65.19% / [[95, 135], [46, 244]] ------------------------------ Epoch 092 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.476354 - Iter 024 / 025, Loss: 0.486582 * Train accuracy / confusion: 76.62% / [[258, 97], [90, 355]], * Val accuracy / confusion: 67.69% / [[126, 104], [64, 226]] ------------------------------ Epoch 093 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473483 - Iter 024 / 025, Loss: 0.649717 * Train accuracy / confusion: 76.50% / [[255, 104], [84, 357]], * Val accuracy / confusion: 68.27% / [[136, 94], [71, 219]] ------------------------------ Epoch 094 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.522298 - Iter 024 / 025, Loss: 0.473380 * Train accuracy / confusion: 73.75% / [[239, 116], [94, 351]], * Val accuracy / confusion: 64.23% / [[189, 41], [145, 145]] ------------------------------ Epoch 095 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.381247 - Iter 024 / 025, Loss: 0.359185 * Train accuracy / confusion: 76.38% / [[245, 109], [80, 366]], * Val accuracy / confusion: 67.69% / [[93, 137], [31, 259]] ------------------------------ Epoch 096 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.311136 - Iter 024 / 025, Loss: 0.358839 * Train accuracy / confusion: 77.25% / [[254, 100], [82, 364]], * Val accuracy / confusion: 65.19% / [[97, 133], [48, 242]] ------------------------------ Epoch 097 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.445502 - Iter 024 / 025, Loss: 0.382616 * Train accuracy / confusion: 75.62% / [[243, 114], [81, 362]], * Val accuracy / confusion: 69.04% / [[137, 93], [68, 222]] ------------------------------ Epoch 098 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.522721 - Iter 024 / 025, Loss: 0.357750 * Train accuracy / confusion: 74.88% / [[255, 102], [99, 344]], * Val accuracy / confusion: 65.00% / [[74, 156], [26, 264]] ------------------------------ Epoch 099 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.536256 - Iter 024 / 025, Loss: 0.462848 * Train accuracy / confusion: 74.75% / [[246, 113], [89, 352]], * Val accuracy / confusion: 71.54% / [[147, 83], [65, 225]] ------------------------------ Epoch 100 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.478580 - Iter 024 / 025, Loss: 0.541791 * Train accuracy / confusion: 75.12% / [[260, 97], [102, 341]], * Val accuracy / confusion: 66.73% / [[108, 122], [51, 239]] ------------------------------ Epoch 101 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.563174 - Iter 024 / 025, Loss: 0.514432 * Train accuracy / confusion: 77.25% / [[253, 101], [81, 365]], * Val accuracy / confusion: 64.23% / [[86, 144], [42, 248]] ------------------------------ Epoch 102 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.392554 - Iter 024 / 025, Loss: 0.420925 * Train accuracy / confusion: 74.12% / [[234, 125], [82, 359]], * Val accuracy / confusion: 66.73% / [[85, 145], [28, 262]] ------------------------------ Epoch 103 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.431231 - Iter 024 / 025, Loss: 0.492570 * Train accuracy / confusion: 77.00% / [[264, 93], [91, 352]], * Val accuracy / confusion: 69.23% / [[155, 75], [85, 205]] ------------------------------ Epoch 104 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.388557 - Iter 024 / 025, Loss: 0.437928 * Train accuracy / confusion: 76.62% / [[255, 98], [89, 358]], * Val accuracy / confusion: 68.08% / [[125, 105], [61, 229]] ------------------------------ Epoch 105 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.559589 - Iter 024 / 025, Loss: 0.593659 * Train accuracy / confusion: 75.38% / [[245, 113], [84, 358]], * Val accuracy / confusion: 66.15% / [[179, 51], [125, 165]] ------------------------------ Epoch 106 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.597588 - Iter 024 / 025, Loss: 0.427115 * Train accuracy / confusion: 77.25% / [[252, 106], [76, 366]], * Val accuracy / confusion: 69.23% / [[108, 122], [38, 252]] ------------------------------ Epoch 107 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.581540 - Iter 024 / 025, Loss: 0.408814 * Train accuracy / confusion: 78.62% / [[257, 98], [73, 372]], * Val accuracy / confusion: 62.69% / [[81, 149], [45, 245]] ------------------------------ Epoch 108 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.510267 - Iter 024 / 025, Loss: 0.389643 * Train accuracy / confusion: 76.75% / [[268, 90], [96, 346]], * Val accuracy / confusion: 66.54% / [[113, 117], [57, 233]] ------------------------------ Epoch 109 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.523908 - Iter 024 / 025, Loss: 0.594883 * Train accuracy / confusion: 75.50% / [[246, 112], [84, 358]], * Val accuracy / confusion: 67.69% / [[136, 94], [74, 216]] ------------------------------ Epoch 110 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.431782 - Iter 024 / 025, Loss: 0.458621 * Train accuracy / confusion: 77.88% / [[254, 105], [72, 369]], * Val accuracy / confusion: 63.27% / [[206, 24], [167, 123]] ------------------------------ Epoch 111 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.533923 - Iter 024 / 025, Loss: 0.402339 * Train accuracy / confusion: 77.50% / [[257, 98], [82, 363]], * Val accuracy / confusion: 66.92% / [[95, 135], [37, 253]] ------------------------------ Epoch 112 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.317379 - Iter 024 / 025, Loss: 0.360521 * Train accuracy / confusion: 78.25% / [[274, 86], [88, 352]], * Val accuracy / confusion: 70.38% / [[139, 91], [63, 227]] ------------------------------ Epoch 113 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.387073 - Iter 024 / 025, Loss: 0.328419 * Train accuracy / confusion: 77.00% / [[257, 98], [86, 359]], * Val accuracy / confusion: 69.81% / [[173, 57], [100, 190]] ------------------------------ Epoch 114 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.530503 - Iter 024 / 025, Loss: 0.476942 * Train accuracy / confusion: 77.62% / [[263, 96], [83, 358]], * Val accuracy / confusion: 69.23% / [[157, 73], [87, 203]] ------------------------------ Epoch 115 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.401252 - Iter 024 / 025, Loss: 0.349728 * Train accuracy / confusion: 76.50% / [[261, 93], [95, 351]], * Val accuracy / confusion: 66.35% / [[162, 68], [107, 183]] ------------------------------ Epoch 116 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.370233 - Iter 024 / 025, Loss: 0.526147 * Train accuracy / confusion: 75.62% / [[255, 97], [98, 350]], * Val accuracy / confusion: 66.15% / [[89, 141], [35, 255]] ------------------------------ Epoch 117 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.428703 - Iter 024 / 025, Loss: 0.498686 * Train accuracy / confusion: 77.50% / [[257, 102], [78, 363]], * Val accuracy / confusion: 67.69% / [[112, 118], [50, 240]] ------------------------------ Epoch 118 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.487685 - Iter 024 / 025, Loss: 0.400848 * Train accuracy / confusion: 78.00% / [[272, 87], [89, 352]], * Val accuracy / confusion: 62.50% / [[192, 38], [157, 133]] ------------------------------ Epoch 119 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.420490 - Iter 024 / 025, Loss: 0.476157 * Train accuracy / confusion: 77.62% / [[268, 87], [92, 353]], * Val accuracy / confusion: 67.50% / [[165, 65], [104, 186]] ------------------------------ Epoch 120 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519304 - Iter 024 / 025, Loss: 0.337743 * Train accuracy / confusion: 76.00% / [[253, 103], [89, 355]], * Val accuracy / confusion: 64.04% / [[89, 141], [46, 244]] ------------------------------ Epoch 121 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.480605 - Iter 024 / 025, Loss: 0.412978 * Train accuracy / confusion: 76.75% / [[261, 92], [94, 353]], * Val accuracy / confusion: 69.23% / [[152, 78], [82, 208]] ------------------------------ Epoch 122 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.439002 - Iter 024 / 025, Loss: 0.490810 * Train accuracy / confusion: 77.75% / [[261, 96], [82, 361]], * Val accuracy / confusion: 67.12% / [[91, 139], [32, 258]] ------------------------------ Epoch 123 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.319207 - Iter 024 / 025, Loss: 0.727578 * Train accuracy / confusion: 78.38% / [[264, 92], [81, 363]], * Val accuracy / confusion: 68.46% / [[160, 70], [94, 196]] ------------------------------ Epoch 124 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.509197 - Iter 024 / 025, Loss: 0.380812 * Train accuracy / confusion: 75.00% / [[246, 108], [92, 354]], * Val accuracy / confusion: 64.04% / [[170, 60], [127, 163]] ------------------------------ Epoch 125 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.473804 - Iter 024 / 025, Loss: 0.424817 * Train accuracy / confusion: 75.50% / [[243, 111], [85, 361]], * Val accuracy / confusion: 70.00% / [[140, 90], [66, 224]] ------------------------------ Epoch 126 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.550129 - Iter 024 / 025, Loss: 0.538348 * Train accuracy / confusion: 80.12% / [[275, 83], [76, 366]], * Val accuracy / confusion: 69.81% / [[123, 107], [50, 240]] ------------------------------ Epoch 127 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.407604 - Iter 024 / 025, Loss: 0.481721 * Train accuracy / confusion: 77.38% / [[261, 97], [84, 358]], * Val accuracy / confusion: 67.50% / [[100, 130], [39, 251]] ------------------------------ Epoch 128 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.453162 - Iter 024 / 025, Loss: 0.421470 * Train accuracy / confusion: 79.25% / [[253, 103], [63, 381]], * Val accuracy / confusion: 61.92% / [[75, 155], [43, 247]] ------------------------------ Epoch 129 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.417890 - Iter 024 / 025, Loss: 0.639585 * Train accuracy / confusion: 78.00% / [[279, 75], [101, 345]], * Val accuracy / confusion: 66.73% / [[161, 69], [104, 186]] ------------------------------ Epoch 130 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.316402 - Iter 024 / 025, Loss: 0.399141 * Train accuracy / confusion: 79.00% / [[262, 92], [76, 370]], * Val accuracy / confusion: 65.77% / [[113, 117], [61, 229]] ------------------------------ Epoch 131 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.409884 - Iter 024 / 025, Loss: 0.437319 * Train accuracy / confusion: 78.00% / [[266, 91], [85, 358]], * Val accuracy / confusion: 65.58% / [[90, 140], [39, 251]] ------------------------------ Epoch 132 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.431238 - Iter 024 / 025, Loss: 0.531950 * Train accuracy / confusion: 76.25% / [[283, 73], [117, 327]], * Val accuracy / confusion: 67.31% / [[111, 119], [51, 239]] ------------------------------ Epoch 133 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.322404 - Iter 024 / 025, Loss: 0.434797 * Train accuracy / confusion: 76.62% / [[259, 95], [92, 354]], * Val accuracy / confusion: 67.31% / [[178, 52], [118, 172]] ------------------------------ Epoch 134 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.477295 - Iter 024 / 025, Loss: 0.492188 * Train accuracy / confusion: 79.38% / [[261, 95], [70, 374]], * Val accuracy / confusion: 66.35% / [[123, 107], [68, 222]] ------------------------------ Epoch 135 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.563779 - Iter 024 / 025, Loss: 0.415327 * Train accuracy / confusion: 76.00% / [[260, 100], [92, 348]], * Val accuracy / confusion: 66.54% / [[105, 125], [49, 241]] ------------------------------ Epoch 136 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.529095 - Iter 024 / 025, Loss: 0.435869 * Train accuracy / confusion: 75.12% / [[261, 97], [102, 340]], * Val accuracy / confusion: 66.15% / [[94, 136], [40, 250]] ------------------------------ Epoch 137 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.428325 - Iter 024 / 025, Loss: 0.265468 * Train accuracy / confusion: 79.38% / [[274, 82], [83, 361]], * Val accuracy / confusion: 67.12% / [[162, 68], [103, 187]] ------------------------------ Epoch 138 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.412479 - Iter 024 / 025, Loss: 0.525571 * Train accuracy / confusion: 77.50% / [[260, 97], [83, 360]], * Val accuracy / confusion: 62.69% / [[54, 176], [18, 272]] ------------------------------ Epoch 139 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.456529 - Iter 024 / 025, Loss: 0.370137 * Train accuracy / confusion: 78.62% / [[263, 90], [81, 366]], * Val accuracy / confusion: 69.81% / [[130, 100], [57, 233]] ------------------------------ Epoch 140 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.514845 - Iter 024 / 025, Loss: 0.412807 * Train accuracy / confusion: 78.25% / [[255, 101], [73, 371]], * Val accuracy / confusion: 67.88% / [[187, 43], [124, 166]] ------------------------------ Epoch 141 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.358547 - Iter 024 / 025, Loss: 0.424519 * Train accuracy / confusion: 77.88% / [[251, 101], [76, 372]], * Val accuracy / confusion: 67.50% / [[90, 140], [29, 261]] ------------------------------ Epoch 142 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.275388 - Iter 024 / 025, Loss: 0.443637 * Train accuracy / confusion: 77.25% / [[249, 104], [78, 369]], * Val accuracy / confusion: 67.50% / [[112, 118], [51, 239]] ------------------------------ Epoch 143 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.398768 - Iter 024 / 025, Loss: 0.553149 * Train accuracy / confusion: 76.50% / [[241, 114], [74, 371]], * Val accuracy / confusion: 63.27% / [[50, 180], [11, 279]] ------------------------------ Epoch 144 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.469049 - Iter 024 / 025, Loss: 0.473722 * Train accuracy / confusion: 78.88% / [[259, 99], [70, 372]], * Val accuracy / confusion: 65.38% / [[128, 102], [78, 212]] ------------------------------ Epoch 145 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.484781 - Iter 024 / 025, Loss: 0.438502 * Train accuracy / confusion: 78.38% / [[268, 86], [87, 359]], * Val accuracy / confusion: 63.46% / [[108, 122], [68, 222]] ------------------------------ Epoch 146 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.351364 - Iter 024 / 025, Loss: 0.372568 * Train accuracy / confusion: 79.50% / [[262, 92], [72, 374]], * Val accuracy / confusion: 69.42% / [[148, 82], [77, 213]] ------------------------------ Epoch 147 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.563589 - Iter 024 / 025, Loss: 0.407739 * Train accuracy / confusion: 78.75% / [[275, 82], [88, 355]], * Val accuracy / confusion: 65.77% / [[125, 105], [73, 217]] ------------------------------ Epoch 148 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.409159 - Iter 024 / 025, Loss: 0.338041 * Train accuracy / confusion: 80.25% / [[267, 86], [72, 375]], * Val accuracy / confusion: 65.19% / [[123, 107], [74, 216]] ------------------------------ Epoch 149 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.479871 - Iter 024 / 025, Loss: 0.382769 * Train accuracy / confusion: 78.25% / [[256, 102], [72, 370]], * Val accuracy / confusion: 66.54% / [[147, 83], [91, 199]] ------------------------------ Epoch 150 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.451039 - Iter 024 / 025, Loss: 0.794522 * Train accuracy / confusion: 78.38% / [[248, 106], [67, 379]], * Val accuracy / confusion: 69.62% / [[111, 119], [39, 251]] ------------------------------ Epoch 151 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.426563 - Iter 024 / 025, Loss: 0.438761 * Train accuracy / confusion: 77.50% / [[252, 107], [73, 368]], * Val accuracy / confusion: 66.15% / [[98, 132], [44, 246]] ------------------------------ Epoch 152 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.481439 - Iter 024 / 025, Loss: 0.463277 * Train accuracy / confusion: 78.62% / [[272, 87], [84, 357]], * Val accuracy / confusion: 67.31% / [[128, 102], [68, 222]] ------------------------------ Epoch 153 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.541984 - Iter 024 / 025, Loss: 0.303459 * Train accuracy / confusion: 79.38% / [[270, 84], [81, 365]], * Val accuracy / confusion: 67.69% / [[187, 43], [125, 165]] ------------------------------ Epoch 154 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.354492 - Iter 024 / 025, Loss: 0.347039 * Train accuracy / confusion: 78.25% / [[260, 98], [76, 366]], * Val accuracy / confusion: 65.38% / [[87, 143], [37, 253]] ------------------------------ Epoch 155 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.555778 - Iter 024 / 025, Loss: 0.525728 * Train accuracy / confusion: 78.12% / [[268, 93], [82, 357]], * Val accuracy / confusion: 66.73% / [[176, 54], [119, 171]] ------------------------------ Epoch 156 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.526745 - Iter 024 / 025, Loss: 0.473563 * Train accuracy / confusion: 77.62% / [[249, 104], [75, 372]], * Val accuracy / confusion: 65.96% / [[86, 144], [33, 257]] ------------------------------ Epoch 157 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.510276 - Iter 024 / 025, Loss: 0.453199 * Train accuracy / confusion: 78.62% / [[254, 103], [68, 375]], * Val accuracy / confusion: 69.62% / [[149, 81], [77, 213]] ------------------------------ Epoch 158 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.441046 - Iter 024 / 025, Loss: 0.521350 * Train accuracy / confusion: 79.12% / [[267, 87], [80, 366]], * Val accuracy / confusion: 67.12% / [[157, 73], [98, 192]] ------------------------------ Epoch 159 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.494458 - Iter 024 / 025, Loss: 0.477368 * Train accuracy / confusion: 78.25% / [[263, 90], [84, 363]], * Val accuracy / confusion: 67.31% / [[134, 96], [74, 216]] ------------------------------ Epoch 160 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.571189 - Iter 024 / 025, Loss: 0.399800 * Train accuracy / confusion: 81.00% / [[278, 78], [74, 370]], * Val accuracy / confusion: 65.38% / [[105, 125], [55, 235]] ------------------------------ Epoch 161 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.511698 - Iter 024 / 025, Loss: 0.332941 * Train accuracy / confusion: 78.75% / [[268, 92], [78, 362]], * Val accuracy / confusion: 64.42% / [[107, 123], [62, 228]] ------------------------------ Epoch 162 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.381498 - Iter 024 / 025, Loss: 0.485803 * Train accuracy / confusion: 77.38% / [[262, 93], [88, 357]], * Val accuracy / confusion: 61.92% / [[178, 52], [146, 144]] ------------------------------ Epoch 163 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.611596 - Iter 024 / 025, Loss: 0.504949 * Train accuracy / confusion: 78.62% / [[265, 95], [76, 364]], * Val accuracy / confusion: 65.58% / [[145, 85], [94, 196]] ------------------------------ Epoch 164 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.399612 - Iter 024 / 025, Loss: 0.355952 * Train accuracy / confusion: 80.88% / [[281, 78], [75, 366]], * Val accuracy / confusion: 68.46% / [[107, 123], [41, 249]] ------------------------------ Epoch 165 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.553550 - Iter 024 / 025, Loss: 0.410883 * Train accuracy / confusion: 79.00% / [[259, 91], [77, 373]], * Val accuracy / confusion: 68.27% / [[117, 113], [52, 238]] ------------------------------ Epoch 166 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.404409 - Iter 024 / 025, Loss: 0.471468 * Train accuracy / confusion: 77.88% / [[264, 91], [86, 359]], * Val accuracy / confusion: 66.35% / [[159, 71], [104, 186]] ------------------------------ Epoch 167 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.345434 - Iter 024 / 025, Loss: 0.550564 * Train accuracy / confusion: 82.88% / [[280, 72], [65, 383]], * Val accuracy / confusion: 64.81% / [[80, 150], [33, 257]] ------------------------------ Epoch 168 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.560564 - Iter 024 / 025, Loss: 0.553663 * Train accuracy / confusion: 76.88% / [[271, 91], [94, 344]], * Val accuracy / confusion: 66.54% / [[128, 102], [72, 218]] ------------------------------ Epoch 169 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.386861 - Iter 024 / 025, Loss: 0.500196 * Train accuracy / confusion: 77.88% / [[260, 97], [80, 363]], * Val accuracy / confusion: 65.58% / [[110, 120], [59, 231]] ------------------------------ Epoch 170 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483265 - Iter 024 / 025, Loss: 0.649573 * Train accuracy / confusion: 79.00% / [[271, 85], [83, 361]], * Val accuracy / confusion: 67.50% / [[150, 80], [89, 201]] ------------------------------ Epoch 171 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519356 - Iter 024 / 025, Loss: 0.391472 * Train accuracy / confusion: 80.25% / [[283, 76], [82, 359]], * Val accuracy / confusion: 66.73% / [[174, 56], [117, 173]] ------------------------------ Epoch 172 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.529035 - Iter 024 / 025, Loss: 0.382042 * Train accuracy / confusion: 78.00% / [[265, 92], [84, 359]], * Val accuracy / confusion: 67.31% / [[136, 94], [76, 214]] ------------------------------ Epoch 173 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.519097 - Iter 024 / 025, Loss: 0.443071 * Train accuracy / confusion: 80.00% / [[262, 94], [66, 378]], * Val accuracy / confusion: 64.42% / [[136, 94], [91, 199]] ------------------------------ Epoch 174 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.242401 - Iter 024 / 025, Loss: 0.544302 * Train accuracy / confusion: 79.62% / [[270, 82], [81, 367]], * Val accuracy / confusion: 64.04% / [[109, 121], [66, 224]] ------------------------------ Epoch 175 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.465608 - Iter 024 / 025, Loss: 0.389742 * Train accuracy / confusion: 79.75% / [[264, 91], [71, 374]], * Val accuracy / confusion: 67.50% / [[112, 118], [51, 239]] ------------------------------ Epoch 176 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.436401 - Iter 024 / 025, Loss: 0.412116 * Train accuracy / confusion: 79.12% / [[277, 80], [87, 356]], * Val accuracy / confusion: 63.85% / [[156, 74], [114, 176]] ------------------------------ Epoch 177 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.331568 - Iter 024 / 025, Loss: 0.466001 * Train accuracy / confusion: 79.50% / [[281, 75], [89, 355]], * Val accuracy / confusion: 65.58% / [[170, 60], [119, 171]] ------------------------------ Epoch 178 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.382032 - Iter 024 / 025, Loss: 0.371442 * Train accuracy / confusion: 79.50% / [[280, 75], [89, 356]], * Val accuracy / confusion: 68.08% / [[181, 49], [117, 173]] ------------------------------ Epoch 179 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.433479 - Iter 024 / 025, Loss: 0.614960 * Train accuracy / confusion: 79.62% / [[258, 96], [67, 379]], * Val accuracy / confusion: 67.88% / [[99, 131], [36, 254]] ------------------------------ Epoch 180 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.524880 - Iter 024 / 025, Loss: 0.296478 * Train accuracy / confusion: 78.75% / [[280, 81], [89, 350]], * Val accuracy / confusion: 67.31% / [[123, 107], [63, 227]] ------------------------------ Epoch 181 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.351282 - Iter 024 / 025, Loss: 0.637624 * Train accuracy / confusion: 80.50% / [[287, 71], [85, 357]], * Val accuracy / confusion: 65.77% / [[140, 90], [88, 202]] ------------------------------ Epoch 182 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.451747 - Iter 024 / 025, Loss: 0.300419 * Train accuracy / confusion: 80.75% / [[272, 83], [71, 374]], * Val accuracy / confusion: 62.69% / [[50, 180], [14, 276]] ------------------------------ Epoch 183 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.343594 - Iter 024 / 025, Loss: 0.342370 * Train accuracy / confusion: 79.75% / [[265, 90], [72, 373]], * Val accuracy / confusion: 68.85% / [[115, 115], [47, 243]] ------------------------------ Epoch 184 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.434856 - Iter 024 / 025, Loss: 0.508655 * Train accuracy / confusion: 81.00% / [[276, 82], [70, 372]], * Val accuracy / confusion: 61.54% / [[167, 63], [137, 153]] ------------------------------ Epoch 185 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.351264 - Iter 024 / 025, Loss: 0.379049 * Train accuracy / confusion: 80.25% / [[282, 77], [81, 360]], * Val accuracy / confusion: 59.23% / [[199, 31], [181, 109]] ------------------------------ Epoch 186 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.453761 - Iter 024 / 025, Loss: 0.422676 * Train accuracy / confusion: 79.50% / [[272, 84], [80, 364]], * Val accuracy / confusion: 67.69% / [[159, 71], [97, 193]] ------------------------------ Epoch 187 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.370853 - Iter 024 / 025, Loss: 0.507291 * Train accuracy / confusion: 79.50% / [[270, 86], [78, 366]], * Val accuracy / confusion: 67.12% / [[99, 131], [40, 250]] ------------------------------ Epoch 188 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.434294 - Iter 024 / 025, Loss: 0.410977 * Train accuracy / confusion: 79.38% / [[276, 79], [86, 359]], * Val accuracy / confusion: 68.08% / [[142, 88], [78, 212]] ------------------------------ Epoch 189 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.428216 - Iter 024 / 025, Loss: 0.334785 * Train accuracy / confusion: 81.00% / [[277, 78], [74, 371]], * Val accuracy / confusion: 58.85% / [[189, 41], [173, 117]] ------------------------------ Epoch 190 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.585487 - Iter 024 / 025, Loss: 0.274101 * Train accuracy / confusion: 80.50% / [[280, 75], [81, 364]], * Val accuracy / confusion: 64.04% / [[64, 166], [21, 269]] ------------------------------ Epoch 191 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.483055 - Iter 024 / 025, Loss: 0.359859 * Train accuracy / confusion: 81.25% / [[284, 74], [76, 366]], * Val accuracy / confusion: 63.65% / [[157, 73], [116, 174]] ------------------------------ Epoch 192 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.344150 - Iter 024 / 025, Loss: 0.459704 * Train accuracy / confusion: 82.38% / [[284, 75], [66, 375]], * Val accuracy / confusion: 61.92% / [[115, 115], [83, 207]] ------------------------------ Epoch 193 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.491057 - Iter 024 / 025, Loss: 0.403146 * Train accuracy / confusion: 81.38% / [[288, 71], [78, 363]], * Val accuracy / confusion: 69.62% / [[112, 118], [40, 250]] ------------------------------ Epoch 194 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.381713 - Iter 024 / 025, Loss: 0.368757 * Train accuracy / confusion: 80.62% / [[284, 73], [82, 361]], * Val accuracy / confusion: 60.19% / [[194, 36], [171, 119]] ------------------------------ Epoch 195 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.488203 - Iter 024 / 025, Loss: 0.383548 * Train accuracy / confusion: 80.38% / [[283, 74], [83, 360]], * Val accuracy / confusion: 65.96% / [[128, 102], [75, 215]] ------------------------------ Epoch 196 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.400500 - Iter 024 / 025, Loss: 0.431352 * Train accuracy / confusion: 82.50% / [[289, 63], [77, 371]], * Val accuracy / confusion: 69.04% / [[122, 108], [53, 237]] ------------------------------ Epoch 197 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.380671 - Iter 024 / 025, Loss: 0.326505 * Train accuracy / confusion: 81.50% / [[281, 73], [75, 371]], * Val accuracy / confusion: 68.27% / [[173, 57], [108, 182]] ------------------------------ Epoch 198 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.401055 - Iter 024 / 025, Loss: 0.363163 * Train accuracy / confusion: 80.12% / [[291, 70], [89, 350]], * Val accuracy / confusion: 64.42% / [[84, 146], [39, 251]] ------------------------------ Epoch 199 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.586505 - Iter 024 / 025, Loss: 0.571082 * Train accuracy / confusion: 80.50% / [[274, 84], [72, 370]], * Val accuracy / confusion: 64.81% / [[178, 52], [131, 159]] ------------------------------ Epoch 200 / 500, Learning rate: 1.00e-03 ------------------------------ - Iter 012 / 025, Loss: 0.628819 - Iter 024 / 025, Loss: 0.350387 * Train accuracy / confusion: 81.75% / [[277, 78], [68, 377]], * Val accuracy / confusion: 68.08% / [[156, 74], [92, 198]] ------------------------------ Epoch 201 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.444057 - Iter 024 / 025, Loss: 0.491132 * Train accuracy / confusion: 81.50% / [[283, 77], [71, 369]], * Val accuracy / confusion: 68.08% / [[142, 88], [78, 212]] ------------------------------ Epoch 202 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.416150 - Iter 024 / 025, Loss: 0.291137 * Train accuracy / confusion: 82.50% / [[276, 81], [59, 384]], * Val accuracy / confusion: 69.81% / [[128, 102], [55, 235]] ------------------------------ Epoch 203 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.311642 - Iter 024 / 025, Loss: 0.287807 * Train accuracy / confusion: 82.88% / [[286, 74], [63, 377]], * Val accuracy / confusion: 67.31% / [[125, 105], [65, 225]] ------------------------------ Epoch 204 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.483162 - Iter 024 / 025, Loss: 0.563701 * Train accuracy / confusion: 81.88% / [[279, 77], [68, 376]], * Val accuracy / confusion: 66.54% / [[134, 96], [78, 212]] ------------------------------ Epoch 205 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.343413 - Iter 024 / 025, Loss: 0.469725 * Train accuracy / confusion: 81.75% / [[281, 75], [71, 373]], * Val accuracy / confusion: 68.27% / [[139, 91], [74, 216]] ------------------------------ Epoch 206 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.425866 - Iter 024 / 025, Loss: 0.359345 * Train accuracy / confusion: 81.75% / [[282, 68], [78, 372]], * Val accuracy / confusion: 65.77% / [[132, 98], [80, 210]] ------------------------------ Epoch 207 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.364357 - Iter 024 / 025, Loss: 0.375226 * Train accuracy / confusion: 84.25% / [[296, 60], [66, 378]], * Val accuracy / confusion: 66.92% / [[128, 102], [70, 220]] ------------------------------ Epoch 208 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.331605 - Iter 024 / 025, Loss: 0.382927 * Train accuracy / confusion: 81.75% / [[278, 76], [70, 376]], * Val accuracy / confusion: 67.88% / [[123, 107], [60, 230]] ------------------------------ Epoch 209 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.344783 - Iter 024 / 025, Loss: 0.297876 * Train accuracy / confusion: 81.25% / [[279, 78], [72, 371]], * Val accuracy / confusion: 68.65% / [[140, 90], [73, 217]] ------------------------------ Epoch 210 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.325324 - Iter 024 / 025, Loss: 0.334170 * Train accuracy / confusion: 82.75% / [[282, 75], [63, 380]], * Val accuracy / confusion: 66.15% / [[135, 95], [81, 209]] ------------------------------ Epoch 211 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.419974 - Iter 024 / 025, Loss: 0.394172 * Train accuracy / confusion: 83.50% / [[290, 67], [65, 378]], * Val accuracy / confusion: 67.31% / [[127, 103], [67, 223]] ------------------------------ Epoch 212 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357356 - Iter 024 / 025, Loss: 0.256131 * Train accuracy / confusion: 83.25% / [[286, 68], [66, 380]], * Val accuracy / confusion: 72.12% / [[143, 87], [58, 232]] ------------------------------ Epoch 213 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.377399 - Iter 024 / 025, Loss: 0.383568 * Train accuracy / confusion: 80.50% / [[277, 78], [78, 367]], * Val accuracy / confusion: 67.88% / [[134, 96], [71, 219]] ------------------------------ Epoch 214 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.488448 - Iter 024 / 025, Loss: 0.349420 * Train accuracy / confusion: 82.62% / [[281, 76], [63, 380]], * Val accuracy / confusion: 69.23% / [[134, 96], [64, 226]] ------------------------------ Epoch 215 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.545999 - Iter 024 / 025, Loss: 0.295640 * Train accuracy / confusion: 83.25% / [[288, 68], [66, 378]], * Val accuracy / confusion: 70.77% / [[135, 95], [57, 233]] ------------------------------ Epoch 216 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.450231 - Iter 024 / 025, Loss: 0.225111 * Train accuracy / confusion: 83.12% / [[287, 65], [70, 378]], * Val accuracy / confusion: 68.08% / [[123, 107], [59, 231]] ------------------------------ Epoch 217 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357331 - Iter 024 / 025, Loss: 0.384671 * Train accuracy / confusion: 82.50% / [[279, 80], [60, 381]], * Val accuracy / confusion: 67.88% / [[136, 94], [73, 217]] ------------------------------ Epoch 218 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.276011 - Iter 024 / 025, Loss: 0.269186 * Train accuracy / confusion: 83.00% / [[289, 70], [66, 375]], * Val accuracy / confusion: 68.46% / [[139, 91], [73, 217]] ------------------------------ Epoch 219 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.387519 - Iter 024 / 025, Loss: 0.314413 * Train accuracy / confusion: 82.25% / [[284, 75], [67, 374]], * Val accuracy / confusion: 69.04% / [[131, 99], [62, 228]] ------------------------------ Epoch 220 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357665 - Iter 024 / 025, Loss: 0.279711 * Train accuracy / confusion: 84.00% / [[295, 63], [65, 377]], * Val accuracy / confusion: 69.42% / [[140, 90], [69, 221]] ------------------------------ Epoch 221 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.680959 - Iter 024 / 025, Loss: 0.257564 * Train accuracy / confusion: 83.12% / [[290, 66], [69, 375]], * Val accuracy / confusion: 68.85% / [[140, 90], [72, 218]] ------------------------------ Epoch 222 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.251671 - Iter 024 / 025, Loss: 0.261776 * Train accuracy / confusion: 83.88% / [[291, 66], [63, 380]], * Val accuracy / confusion: 68.46% / [[126, 104], [60, 230]] ------------------------------ Epoch 223 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.234876 - Iter 024 / 025, Loss: 0.371101 * Train accuracy / confusion: 84.12% / [[290, 65], [62, 383]], * Val accuracy / confusion: 66.35% / [[123, 107], [68, 222]] ------------------------------ Epoch 224 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.312731 - Iter 024 / 025, Loss: 0.291657 * Train accuracy / confusion: 83.12% / [[289, 71], [64, 376]], * Val accuracy / confusion: 67.69% / [[143, 87], [81, 209]] ------------------------------ Epoch 225 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.409158 - Iter 024 / 025, Loss: 0.288201 * Train accuracy / confusion: 83.25% / [[291, 68], [66, 375]], * Val accuracy / confusion: 67.69% / [[146, 84], [84, 206]] ------------------------------ Epoch 226 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.315453 - Iter 024 / 025, Loss: 0.209518 * Train accuracy / confusion: 85.12% / [[296, 55], [64, 385]], * Val accuracy / confusion: 65.77% / [[137, 93], [85, 205]] ------------------------------ Epoch 227 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.289273 - Iter 024 / 025, Loss: 0.371911 * Train accuracy / confusion: 84.00% / [[300, 54], [74, 372]], * Val accuracy / confusion: 66.15% / [[148, 82], [94, 196]] ------------------------------ Epoch 228 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.344812 - Iter 024 / 025, Loss: 0.388631 * Train accuracy / confusion: 82.00% / [[285, 70], [74, 371]], * Val accuracy / confusion: 70.19% / [[140, 90], [65, 225]] ------------------------------ Epoch 229 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.314600 - Iter 024 / 025, Loss: 0.372178 * Train accuracy / confusion: 83.50% / [[284, 73], [59, 384]], * Val accuracy / confusion: 67.50% / [[132, 98], [71, 219]] ------------------------------ Epoch 230 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.329384 - Iter 024 / 025, Loss: 0.294914 * Train accuracy / confusion: 85.12% / [[293, 62], [57, 388]], * Val accuracy / confusion: 69.23% / [[139, 91], [69, 221]] ------------------------------ Epoch 231 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.252185 - Iter 024 / 025, Loss: 0.368656 * Train accuracy / confusion: 85.00% / [[296, 60], [60, 384]], * Val accuracy / confusion: 66.73% / [[146, 84], [89, 201]] ------------------------------ Epoch 232 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.361213 - Iter 024 / 025, Loss: 0.354346 * Train accuracy / confusion: 84.38% / [[293, 67], [58, 382]], * Val accuracy / confusion: 66.35% / [[123, 107], [68, 222]] ------------------------------ Epoch 233 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.325710 - Iter 024 / 025, Loss: 0.244242 * Train accuracy / confusion: 84.38% / [[288, 66], [59, 387]], * Val accuracy / confusion: 66.73% / [[132, 98], [75, 215]] ------------------------------ Epoch 234 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.224924 - Iter 024 / 025, Loss: 0.413034 * Train accuracy / confusion: 84.62% / [[294, 63], [60, 383]], * Val accuracy / confusion: 69.81% / [[142, 88], [69, 221]] ------------------------------ Epoch 235 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.355524 - Iter 024 / 025, Loss: 0.323758 * Train accuracy / confusion: 84.75% / [[294, 65], [57, 384]], * Val accuracy / confusion: 69.23% / [[135, 95], [65, 225]] ------------------------------ Epoch 236 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.337989 - Iter 024 / 025, Loss: 0.315418 * Train accuracy / confusion: 83.25% / [[286, 74], [60, 380]], * Val accuracy / confusion: 68.46% / [[143, 87], [77, 213]] ------------------------------ Epoch 237 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.465470 - Iter 024 / 025, Loss: 0.421193 * Train accuracy / confusion: 81.88% / [[277, 80], [65, 378]], * Val accuracy / confusion: 70.58% / [[145, 85], [68, 222]] ------------------------------ Epoch 238 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.582261 - Iter 024 / 025, Loss: 0.423851 * Train accuracy / confusion: 83.12% / [[285, 72], [63, 380]], * Val accuracy / confusion: 69.42% / [[150, 80], [79, 211]] ------------------------------ Epoch 239 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.374747 - Iter 024 / 025, Loss: 0.589040 * Train accuracy / confusion: 84.38% / [[290, 67], [58, 385]], * Val accuracy / confusion: 68.08% / [[144, 86], [80, 210]] ------------------------------ Epoch 240 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.388673 - Iter 024 / 025, Loss: 0.293907 * Train accuracy / confusion: 82.88% / [[286, 71], [66, 377]], * Val accuracy / confusion: 69.81% / [[135, 95], [62, 228]] ------------------------------ Epoch 241 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.377282 - Iter 024 / 025, Loss: 0.358610 * Train accuracy / confusion: 82.38% / [[277, 77], [64, 382]], * Val accuracy / confusion: 70.58% / [[148, 82], [71, 219]] ------------------------------ Epoch 242 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.511059 - Iter 024 / 025, Loss: 0.351607 * Train accuracy / confusion: 86.00% / [[304, 56], [56, 384]], * Val accuracy / confusion: 66.92% / [[120, 110], [62, 228]] ------------------------------ Epoch 243 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.397449 - Iter 024 / 025, Loss: 0.387523 * Train accuracy / confusion: 83.38% / [[288, 67], [66, 379]], * Val accuracy / confusion: 67.50% / [[129, 101], [68, 222]] ------------------------------ Epoch 244 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.316099 - Iter 024 / 025, Loss: 0.242127 * Train accuracy / confusion: 83.50% / [[293, 62], [70, 375]], * Val accuracy / confusion: 66.92% / [[134, 96], [76, 214]] ------------------------------ Epoch 245 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.404274 - Iter 024 / 025, Loss: 0.349801 * Train accuracy / confusion: 83.75% / [[291, 64], [66, 379]], * Val accuracy / confusion: 69.23% / [[133, 97], [63, 227]] ------------------------------ Epoch 246 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408713 - Iter 024 / 025, Loss: 0.478528 * Train accuracy / confusion: 84.12% / [[293, 64], [63, 380]], * Val accuracy / confusion: 67.88% / [[128, 102], [65, 225]] ------------------------------ Epoch 247 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.290355 - Iter 024 / 025, Loss: 0.356135 * Train accuracy / confusion: 83.88% / [[294, 66], [63, 377]], * Val accuracy / confusion: 70.00% / [[136, 94], [62, 228]] ------------------------------ Epoch 248 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.261530 - Iter 024 / 025, Loss: 0.363628 * Train accuracy / confusion: 85.50% / [[299, 55], [61, 385]], * Val accuracy / confusion: 64.23% / [[126, 104], [82, 208]] ------------------------------ Epoch 249 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.268896 - Iter 024 / 025, Loss: 0.464739 * Train accuracy / confusion: 83.62% / [[299, 62], [69, 370]], * Val accuracy / confusion: 67.69% / [[127, 103], [65, 225]] ------------------------------ Epoch 250 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.265176 - Iter 024 / 025, Loss: 0.249699 * Train accuracy / confusion: 85.25% / [[302, 52], [66, 380]], * Val accuracy / confusion: 67.88% / [[130, 100], [67, 223]] ------------------------------ Epoch 251 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.487223 - Iter 024 / 025, Loss: 0.317080 * Train accuracy / confusion: 84.88% / [[293, 62], [59, 386]], * Val accuracy / confusion: 67.69% / [[132, 98], [70, 220]] ------------------------------ Epoch 252 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.409494 - Iter 024 / 025, Loss: 0.281155 * Train accuracy / confusion: 83.25% / [[285, 68], [66, 381]], * Val accuracy / confusion: 68.65% / [[144, 86], [77, 213]] ------------------------------ Epoch 253 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408270 - Iter 024 / 025, Loss: 0.576679 * Train accuracy / confusion: 82.62% / [[284, 73], [66, 377]], * Val accuracy / confusion: 67.88% / [[133, 97], [70, 220]] ------------------------------ Epoch 254 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.346567 - Iter 024 / 025, Loss: 0.287885 * Train accuracy / confusion: 83.00% / [[282, 75], [61, 382]], * Val accuracy / confusion: 65.96% / [[129, 101], [76, 214]] ------------------------------ Epoch 255 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.254666 - Iter 024 / 025, Loss: 0.272523 * Train accuracy / confusion: 83.00% / [[292, 63], [73, 372]], * Val accuracy / confusion: 66.73% / [[132, 98], [75, 215]] ------------------------------ Epoch 256 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.280019 - Iter 024 / 025, Loss: 0.564484 * Train accuracy / confusion: 85.62% / [[295, 60], [55, 390]], * Val accuracy / confusion: 64.42% / [[123, 107], [78, 212]] ------------------------------ Epoch 257 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.231854 - Iter 024 / 025, Loss: 0.373014 * Train accuracy / confusion: 83.88% / [[291, 66], [63, 380]], * Val accuracy / confusion: 65.96% / [[158, 72], [105, 185]] ------------------------------ Epoch 258 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.269476 - Iter 024 / 025, Loss: 0.285406 * Train accuracy / confusion: 84.50% / [[299, 61], [63, 377]], * Val accuracy / confusion: 66.54% / [[137, 93], [81, 209]] ------------------------------ Epoch 259 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.406124 - Iter 024 / 025, Loss: 0.326499 * Train accuracy / confusion: 85.25% / [[297, 60], [58, 385]], * Val accuracy / confusion: 66.35% / [[146, 84], [91, 199]] ------------------------------ Epoch 260 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.483720 - Iter 024 / 025, Loss: 0.398440 * Train accuracy / confusion: 84.25% / [[294, 60], [66, 380]], * Val accuracy / confusion: 67.50% / [[130, 100], [69, 221]] ------------------------------ Epoch 261 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.342381 - Iter 024 / 025, Loss: 0.319543 * Train accuracy / confusion: 84.25% / [[297, 66], [60, 377]], * Val accuracy / confusion: 65.77% / [[135, 95], [83, 207]] ------------------------------ Epoch 262 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.212518 - Iter 024 / 025, Loss: 0.440744 * Train accuracy / confusion: 83.50% / [[294, 62], [70, 374]], * Val accuracy / confusion: 67.69% / [[130, 100], [68, 222]] ------------------------------ Epoch 263 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.349489 - Iter 024 / 025, Loss: 0.244733 * Train accuracy / confusion: 84.00% / [[298, 57], [71, 374]], * Val accuracy / confusion: 70.38% / [[143, 87], [67, 223]] ------------------------------ Epoch 264 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.262918 - Iter 024 / 025, Loss: 0.259313 * Train accuracy / confusion: 85.00% / [[300, 57], [63, 380]], * Val accuracy / confusion: 68.85% / [[140, 90], [72, 218]] ------------------------------ Epoch 265 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.177488 - Iter 024 / 025, Loss: 0.338176 * Train accuracy / confusion: 84.00% / [[286, 70], [58, 386]], * Val accuracy / confusion: 68.27% / [[137, 93], [72, 218]] ------------------------------ Epoch 266 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.279477 - Iter 024 / 025, Loss: 0.374873 * Train accuracy / confusion: 83.12% / [[286, 70], [65, 379]], * Val accuracy / confusion: 66.54% / [[130, 100], [74, 216]] ------------------------------ Epoch 267 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.232122 - Iter 024 / 025, Loss: 0.223500 * Train accuracy / confusion: 83.88% / [[296, 63], [66, 375]], * Val accuracy / confusion: 66.92% / [[137, 93], [79, 211]] ------------------------------ Epoch 268 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.262401 - Iter 024 / 025, Loss: 0.381791 * Train accuracy / confusion: 85.25% / [[302, 53], [65, 380]], * Val accuracy / confusion: 64.42% / [[126, 104], [81, 209]] ------------------------------ Epoch 269 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.274331 - Iter 024 / 025, Loss: 0.204146 * Train accuracy / confusion: 83.88% / [[294, 67], [62, 377]], * Val accuracy / confusion: 66.92% / [[127, 103], [69, 221]] ------------------------------ Epoch 270 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.357351 - Iter 024 / 025, Loss: 0.366066 * Train accuracy / confusion: 84.00% / [[288, 65], [63, 384]], * Val accuracy / confusion: 69.23% / [[138, 92], [68, 222]] ------------------------------ Epoch 271 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.276951 - Iter 024 / 025, Loss: 0.370489 * Train accuracy / confusion: 82.38% / [[285, 69], [72, 374]], * Val accuracy / confusion: 67.69% / [[143, 87], [81, 209]] ------------------------------ Epoch 272 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.332805 - Iter 024 / 025, Loss: 0.208747 * Train accuracy / confusion: 84.12% / [[292, 66], [61, 381]], * Val accuracy / confusion: 65.38% / [[136, 94], [86, 204]] ------------------------------ Epoch 273 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.263134 - Iter 024 / 025, Loss: 0.207886 * Train accuracy / confusion: 85.88% / [[310, 47], [66, 377]], * Val accuracy / confusion: 68.65% / [[150, 80], [83, 207]] ------------------------------ Epoch 274 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.271989 - Iter 024 / 025, Loss: 0.314044 * Train accuracy / confusion: 84.75% / [[302, 56], [66, 376]], * Val accuracy / confusion: 68.08% / [[135, 95], [71, 219]] ------------------------------ Epoch 275 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.264762 - Iter 024 / 025, Loss: 0.480958 * Train accuracy / confusion: 85.62% / [[295, 58], [57, 390]], * Val accuracy / confusion: 66.73% / [[128, 102], [71, 219]] ------------------------------ Epoch 276 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.272452 - Iter 024 / 025, Loss: 0.461191 * Train accuracy / confusion: 84.62% / [[300, 53], [70, 377]], * Val accuracy / confusion: 66.54% / [[128, 102], [72, 218]] ------------------------------ Epoch 277 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.226080 - Iter 024 / 025, Loss: 0.333045 * Train accuracy / confusion: 84.25% / [[295, 64], [62, 379]], * Val accuracy / confusion: 69.42% / [[146, 84], [75, 215]] ------------------------------ Epoch 278 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.360229 - Iter 024 / 025, Loss: 0.451329 * Train accuracy / confusion: 85.50% / [[298, 56], [60, 386]], * Val accuracy / confusion: 65.19% / [[133, 97], [84, 206]] ------------------------------ Epoch 279 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.217112 - Iter 024 / 025, Loss: 0.285100 * Train accuracy / confusion: 85.75% / [[293, 63], [51, 393]], * Val accuracy / confusion: 63.85% / [[119, 111], [77, 213]] ------------------------------ Epoch 280 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.542263 - Iter 024 / 025, Loss: 0.211058 * Train accuracy / confusion: 81.50% / [[282, 74], [74, 370]], * Val accuracy / confusion: 68.08% / [[132, 98], [68, 222]] ------------------------------ Epoch 281 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.271087 - Iter 024 / 025, Loss: 0.363901 * Train accuracy / confusion: 83.88% / [[292, 60], [69, 379]], * Val accuracy / confusion: 67.88% / [[126, 104], [63, 227]] ------------------------------ Epoch 282 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.380732 - Iter 024 / 025, Loss: 0.365643 * Train accuracy / confusion: 85.25% / [[301, 57], [61, 381]], * Val accuracy / confusion: 68.85% / [[144, 86], [76, 214]] ------------------------------ Epoch 283 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.383465 - Iter 024 / 025, Loss: 0.290253 * Train accuracy / confusion: 84.88% / [[300, 59], [62, 379]], * Val accuracy / confusion: 68.08% / [[134, 96], [70, 220]] ------------------------------ Epoch 284 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.319990 - Iter 024 / 025, Loss: 0.362918 * Train accuracy / confusion: 84.00% / [[295, 63], [65, 377]], * Val accuracy / confusion: 67.31% / [[142, 88], [82, 208]] ------------------------------ Epoch 285 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.612305 - Iter 024 / 025, Loss: 0.255954 * Train accuracy / confusion: 86.75% / [[299, 58], [48, 395]], * Val accuracy / confusion: 65.96% / [[130, 100], [77, 213]] ------------------------------ Epoch 286 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.316922 - Iter 024 / 025, Loss: 0.380688 * Train accuracy / confusion: 85.12% / [[305, 52], [67, 376]], * Val accuracy / confusion: 66.73% / [[137, 93], [80, 210]] ------------------------------ Epoch 287 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.355646 - Iter 024 / 025, Loss: 0.313930 * Train accuracy / confusion: 83.75% / [[292, 67], [63, 378]], * Val accuracy / confusion: 67.31% / [[137, 93], [77, 213]] ------------------------------ Epoch 288 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.552488 - Iter 024 / 025, Loss: 0.309669 * Train accuracy / confusion: 83.75% / [[288, 64], [66, 382]], * Val accuracy / confusion: 67.31% / [[136, 94], [76, 214]] ------------------------------ Epoch 289 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.271375 - Iter 024 / 025, Loss: 0.206642 * Train accuracy / confusion: 85.12% / [[296, 64], [55, 385]], * Val accuracy / confusion: 68.27% / [[139, 91], [74, 216]] ------------------------------ Epoch 290 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.425711 - Iter 024 / 025, Loss: 0.326618 * Train accuracy / confusion: 85.50% / [[299, 57], [59, 385]], * Val accuracy / confusion: 67.50% / [[136, 94], [75, 215]] ------------------------------ Epoch 291 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.367922 - Iter 024 / 025, Loss: 0.365080 * Train accuracy / confusion: 85.88% / [[305, 52], [61, 382]], * Val accuracy / confusion: 68.85% / [[145, 85], [77, 213]] ------------------------------ Epoch 292 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.350801 - Iter 024 / 025, Loss: 0.388195 * Train accuracy / confusion: 85.88% / [[304, 48], [65, 383]], * Val accuracy / confusion: 65.77% / [[131, 99], [79, 211]] ------------------------------ Epoch 293 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.289219 - Iter 024 / 025, Loss: 0.267595 * Train accuracy / confusion: 85.62% / [[301, 53], [62, 384]], * Val accuracy / confusion: 67.31% / [[144, 86], [84, 206]] ------------------------------ Epoch 294 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.364281 - Iter 024 / 025, Loss: 0.296013 * Train accuracy / confusion: 86.25% / [[305, 53], [57, 385]], * Val accuracy / confusion: 69.42% / [[141, 89], [70, 220]] ------------------------------ Epoch 295 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.365078 - Iter 024 / 025, Loss: 0.255122 * Train accuracy / confusion: 85.88% / [[305, 48], [65, 382]], * Val accuracy / confusion: 66.73% / [[130, 100], [73, 217]] ------------------------------ Epoch 296 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.197768 - Iter 024 / 025, Loss: 0.358430 * Train accuracy / confusion: 85.50% / [[309, 50], [66, 375]], * Val accuracy / confusion: 66.73% / [[125, 105], [68, 222]] ------------------------------ Epoch 297 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.354031 - Iter 024 / 025, Loss: 0.345729 * Train accuracy / confusion: 84.25% / [[296, 52], [74, 378]], * Val accuracy / confusion: 67.88% / [[148, 82], [85, 205]] ------------------------------ Epoch 298 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.334248 - Iter 024 / 025, Loss: 0.240332 * Train accuracy / confusion: 85.62% / [[307, 52], [63, 378]], * Val accuracy / confusion: 68.08% / [[140, 90], [76, 214]] ------------------------------ Epoch 299 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.269152 - Iter 024 / 025, Loss: 0.198576 * Train accuracy / confusion: 84.50% / [[300, 53], [71, 376]], * Val accuracy / confusion: 67.88% / [[143, 87], [80, 210]] ------------------------------ Epoch 300 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.471241 - Iter 024 / 025, Loss: 0.243801 * Train accuracy / confusion: 86.38% / [[311, 43], [66, 380]], * Val accuracy / confusion: 67.31% / [[132, 98], [72, 218]] ------------------------------ Epoch 301 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.242835 - Iter 024 / 025, Loss: 0.320179 * Train accuracy / confusion: 85.38% / [[298, 59], [58, 385]], * Val accuracy / confusion: 68.27% / [[140, 90], [75, 215]] ------------------------------ Epoch 302 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.344873 - Iter 024 / 025, Loss: 0.293881 * Train accuracy / confusion: 85.62% / [[301, 49], [66, 384]], * Val accuracy / confusion: 65.96% / [[130, 100], [77, 213]] ------------------------------ Epoch 303 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.245743 - Iter 024 / 025, Loss: 0.364471 * Train accuracy / confusion: 84.62% / [[301, 56], [67, 376]], * Val accuracy / confusion: 67.50% / [[121, 109], [60, 230]] ------------------------------ Epoch 304 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.287631 - Iter 024 / 025, Loss: 0.264903 * Train accuracy / confusion: 83.88% / [[298, 56], [73, 373]], * Val accuracy / confusion: 70.38% / [[147, 83], [71, 219]] ------------------------------ Epoch 305 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.229454 - Iter 024 / 025, Loss: 0.316517 * Train accuracy / confusion: 86.00% / [[299, 48], [64, 389]], * Val accuracy / confusion: 67.31% / [[142, 88], [82, 208]] ------------------------------ Epoch 306 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.401353 - Iter 024 / 025, Loss: 0.345616 * Train accuracy / confusion: 86.12% / [[293, 62], [49, 396]], * Val accuracy / confusion: 67.69% / [[132, 98], [70, 220]] ------------------------------ Epoch 307 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.321406 - Iter 024 / 025, Loss: 0.231885 * Train accuracy / confusion: 85.62% / [[300, 53], [62, 385]], * Val accuracy / confusion: 67.88% / [[140, 90], [77, 213]] ------------------------------ Epoch 308 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.306481 - Iter 024 / 025, Loss: 0.280056 * Train accuracy / confusion: 86.00% / [[307, 53], [59, 381]], * Val accuracy / confusion: 68.27% / [[142, 88], [77, 213]] ------------------------------ Epoch 309 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.360939 - Iter 024 / 025, Loss: 0.437821 * Train accuracy / confusion: 85.12% / [[298, 55], [64, 383]], * Val accuracy / confusion: 66.54% / [[135, 95], [79, 211]] ------------------------------ Epoch 310 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.408067 - Iter 024 / 025, Loss: 0.300213 * Train accuracy / confusion: 85.50% / [[298, 58], [58, 386]], * Val accuracy / confusion: 65.96% / [[127, 103], [74, 216]] ------------------------------ Epoch 311 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.290922 - Iter 024 / 025, Loss: 0.378923 * Train accuracy / confusion: 88.00% / [[306, 49], [47, 398]], * Val accuracy / confusion: 67.50% / [[137, 93], [76, 214]] ------------------------------ Epoch 312 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.459404 - Iter 024 / 025, Loss: 0.356745 * Train accuracy / confusion: 86.75% / [[302, 56], [50, 392]], * Val accuracy / confusion: 66.35% / [[122, 108], [67, 223]] ------------------------------ Epoch 313 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.502756 - Iter 024 / 025, Loss: 0.334023 * Train accuracy / confusion: 85.00% / [[299, 58], [62, 381]], * Val accuracy / confusion: 67.69% / [[134, 96], [72, 218]] ------------------------------ Epoch 314 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.498350 - Iter 024 / 025, Loss: 0.303093 * Train accuracy / confusion: 85.50% / [[295, 58], [58, 389]], * Val accuracy / confusion: 68.08% / [[140, 90], [76, 214]] ------------------------------ Epoch 315 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.435248 - Iter 024 / 025, Loss: 0.186374 * Train accuracy / confusion: 85.75% / [[299, 56], [58, 387]], * Val accuracy / confusion: 69.23% / [[144, 86], [74, 216]] ------------------------------ Epoch 316 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.158922 - Iter 024 / 025, Loss: 0.241707 * Train accuracy / confusion: 85.25% / [[303, 51], [67, 379]], * Val accuracy / confusion: 67.50% / [[140, 90], [79, 211]] ------------------------------ Epoch 317 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.270246 - Iter 024 / 025, Loss: 0.189441 * Train accuracy / confusion: 85.62% / [[299, 59], [56, 386]], * Val accuracy / confusion: 67.12% / [[131, 99], [72, 218]] ------------------------------ Epoch 318 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.260972 - Iter 024 / 025, Loss: 0.548879 * Train accuracy / confusion: 84.75% / [[297, 63], [59, 381]], * Val accuracy / confusion: 65.38% / [[124, 106], [74, 216]] ------------------------------ Epoch 319 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.273767 - Iter 024 / 025, Loss: 0.216271 * Train accuracy / confusion: 86.88% / [[309, 44], [61, 386]], * Val accuracy / confusion: 67.50% / [[145, 85], [84, 206]] ------------------------------ Epoch 320 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.256280 - Iter 024 / 025, Loss: 0.338799 * Train accuracy / confusion: 86.12% / [[308, 50], [61, 381]], * Val accuracy / confusion: 66.15% / [[136, 94], [82, 208]] ------------------------------ Epoch 321 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.231868 - Iter 024 / 025, Loss: 0.428676 * Train accuracy / confusion: 85.75% / [[301, 53], [61, 385]], * Val accuracy / confusion: 68.08% / [[135, 95], [71, 219]] ------------------------------ Epoch 322 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.351513 - Iter 024 / 025, Loss: 0.282724 * Train accuracy / confusion: 84.38% / [[303, 60], [65, 372]], * Val accuracy / confusion: 67.50% / [[130, 100], [69, 221]] ------------------------------ Epoch 323 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.277311 - Iter 024 / 025, Loss: 0.496362 * Train accuracy / confusion: 85.12% / [[306, 46], [73, 375]], * Val accuracy / confusion: 65.38% / [[133, 97], [83, 207]] ------------------------------ Epoch 324 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.519064 - Iter 024 / 025, Loss: 0.427111 * Train accuracy / confusion: 85.38% / [[298, 59], [58, 385]], * Val accuracy / confusion: 69.62% / [[138, 92], [66, 224]] ------------------------------ Epoch 325 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.239321 - Iter 024 / 025, Loss: 0.257880 * Train accuracy / confusion: 86.88% / [[305, 48], [57, 390]], * Val accuracy / confusion: 67.50% / [[138, 92], [77, 213]] ------------------------------ Epoch 326 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.334067 - Iter 024 / 025, Loss: 0.395677 * Train accuracy / confusion: 87.00% / [[307, 52], [52, 389]], * Val accuracy / confusion: 66.54% / [[133, 97], [77, 213]] ------------------------------ Epoch 327 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.305119 - Iter 024 / 025, Loss: 0.317774 * Train accuracy / confusion: 87.88% / [[307, 47], [50, 396]], * Val accuracy / confusion: 67.31% / [[131, 99], [71, 219]] ------------------------------ Epoch 328 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.489942 - Iter 024 / 025, Loss: 0.286235 * Train accuracy / confusion: 83.75% / [[298, 62], [68, 372]], * Val accuracy / confusion: 71.35% / [[151, 79], [70, 220]] ------------------------------ Epoch 329 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.303459 - Iter 024 / 025, Loss: 0.305345 * Train accuracy / confusion: 84.25% / [[290, 68], [58, 384]], * Val accuracy / confusion: 67.69% / [[142, 88], [80, 210]] ------------------------------ Epoch 330 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.390906 - Iter 024 / 025, Loss: 0.298843 * Train accuracy / confusion: 85.12% / [[298, 58], [61, 383]], * Val accuracy / confusion: 68.85% / [[135, 95], [67, 223]] ------------------------------ Epoch 331 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.246724 - Iter 024 / 025, Loss: 0.501709 * Train accuracy / confusion: 86.62% / [[303, 53], [54, 390]], * Val accuracy / confusion: 68.27% / [[128, 102], [63, 227]] ------------------------------ Epoch 332 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.206685 - Iter 024 / 025, Loss: 0.313257 * Train accuracy / confusion: 87.25% / [[310, 45], [57, 388]], * Val accuracy / confusion: 66.54% / [[141, 89], [85, 205]] ------------------------------ Epoch 333 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.139646 - Iter 024 / 025, Loss: 0.584211 * Train accuracy / confusion: 85.38% / [[309, 53], [64, 374]], * Val accuracy / confusion: 66.92% / [[134, 96], [76, 214]] ------------------------------ Epoch 334 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.426809 - Iter 024 / 025, Loss: 0.273751 * Train accuracy / confusion: 88.00% / [[301, 51], [45, 403]], * Val accuracy / confusion: 67.12% / [[142, 88], [83, 207]] ------------------------------ Epoch 335 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.213488 - Iter 024 / 025, Loss: 0.235705 * Train accuracy / confusion: 85.38% / [[299, 54], [63, 384]], * Val accuracy / confusion: 70.38% / [[137, 93], [61, 229]] ------------------------------ Epoch 336 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.184522 - Iter 024 / 025, Loss: 0.346450 * Train accuracy / confusion: 86.00% / [[302, 51], [61, 386]], * Val accuracy / confusion: 67.50% / [[153, 77], [92, 198]] ------------------------------ Epoch 337 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.231529 - Iter 024 / 025, Loss: 0.216727 * Train accuracy / confusion: 86.00% / [[303, 52], [60, 385]], * Val accuracy / confusion: 70.00% / [[136, 94], [62, 228]] ------------------------------ Epoch 338 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.238128 - Iter 024 / 025, Loss: 0.267110 * Train accuracy / confusion: 85.25% / [[298, 58], [60, 384]], * Val accuracy / confusion: 65.77% / [[124, 106], [72, 218]] ------------------------------ Epoch 339 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.362044 - Iter 024 / 025, Loss: 0.417498 * Train accuracy / confusion: 86.75% / [[310, 44], [62, 384]], * Val accuracy / confusion: 66.54% / [[147, 83], [91, 199]] ------------------------------ Epoch 340 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.232204 - Iter 024 / 025, Loss: 0.213999 * Train accuracy / confusion: 86.75% / [[305, 55], [51, 389]], * Val accuracy / confusion: 65.96% / [[126, 104], [73, 217]] ------------------------------ Epoch 341 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.313610 - Iter 024 / 025, Loss: 0.319856 * Train accuracy / confusion: 87.12% / [[311, 41], [62, 386]], * Val accuracy / confusion: 66.15% / [[134, 96], [80, 210]] ------------------------------ Epoch 342 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.276058 - Iter 024 / 025, Loss: 0.288299 * Train accuracy / confusion: 87.88% / [[309, 48], [49, 394]], * Val accuracy / confusion: 69.04% / [[157, 73], [88, 202]] ------------------------------ Epoch 343 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.309493 - Iter 024 / 025, Loss: 0.333450 * Train accuracy / confusion: 85.62% / [[301, 56], [59, 384]], * Val accuracy / confusion: 66.15% / [[127, 103], [73, 217]] ------------------------------ Epoch 344 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.277569 - Iter 024 / 025, Loss: 0.245857 * Train accuracy / confusion: 88.00% / [[315, 41], [55, 389]], * Val accuracy / confusion: 68.85% / [[141, 89], [73, 217]] ------------------------------ Epoch 345 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.377421 - Iter 024 / 025, Loss: 0.258220 * Train accuracy / confusion: 86.50% / [[306, 54], [54, 386]], * Val accuracy / confusion: 68.65% / [[137, 93], [70, 220]] ------------------------------ Epoch 346 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.308942 - Iter 024 / 025, Loss: 0.469787 * Train accuracy / confusion: 85.50% / [[300, 57], [59, 384]], * Val accuracy / confusion: 68.27% / [[144, 86], [79, 211]] ------------------------------ Epoch 347 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.341627 - Iter 024 / 025, Loss: 0.242547 * Train accuracy / confusion: 87.50% / [[310, 48], [52, 390]], * Val accuracy / confusion: 67.31% / [[128, 102], [68, 222]] ------------------------------ Epoch 348 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.437743 - Iter 024 / 025, Loss: 0.328084 * Train accuracy / confusion: 87.12% / [[304, 51], [52, 393]], * Val accuracy / confusion: 67.31% / [[130, 100], [70, 220]] ------------------------------ Epoch 349 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.462385 - Iter 024 / 025, Loss: 0.258860 * Train accuracy / confusion: 86.62% / [[303, 53], [54, 390]], * Val accuracy / confusion: 65.38% / [[137, 93], [87, 203]] ------------------------------ Epoch 350 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.237667 - Iter 024 / 025, Loss: 0.193128 * Train accuracy / confusion: 87.00% / [[303, 52], [52, 393]], * Val accuracy / confusion: 66.15% / [[127, 103], [73, 217]] ------------------------------ Epoch 351 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.383317 - Iter 024 / 025, Loss: 0.392068 * Train accuracy / confusion: 84.62% / [[301, 53], [70, 376]], * Val accuracy / confusion: 68.46% / [[126, 104], [60, 230]] ------------------------------ Epoch 352 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.257621 - Iter 024 / 025, Loss: 0.343737 * Train accuracy / confusion: 86.38% / [[303, 52], [57, 388]], * Val accuracy / confusion: 69.04% / [[158, 72], [89, 201]] ------------------------------ Epoch 353 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.273693 - Iter 024 / 025, Loss: 0.409192 * Train accuracy / confusion: 86.75% / [[311, 48], [58, 383]], * Val accuracy / confusion: 67.88% / [[139, 91], [76, 214]] ------------------------------ Epoch 354 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.260157 - Iter 024 / 025, Loss: 0.231420 * Train accuracy / confusion: 86.00% / [[300, 58], [54, 388]], * Val accuracy / confusion: 65.58% / [[134, 96], [83, 207]] ------------------------------ Epoch 355 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.232678 - Iter 024 / 025, Loss: 0.180382 * Train accuracy / confusion: 86.38% / [[305, 50], [59, 386]], * Val accuracy / confusion: 67.88% / [[134, 96], [71, 219]] ------------------------------ Epoch 356 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.359388 - Iter 024 / 025, Loss: 0.424603 * Train accuracy / confusion: 85.62% / [[307, 52], [63, 378]], * Val accuracy / confusion: 67.88% / [[138, 92], [75, 215]] ------------------------------ Epoch 357 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.335024 - Iter 024 / 025, Loss: 0.238533 * Train accuracy / confusion: 87.25% / [[311, 47], [55, 387]], * Val accuracy / confusion: 69.04% / [[138, 92], [69, 221]] ------------------------------ Epoch 358 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.355520 - Iter 024 / 025, Loss: 0.299663 * Train accuracy / confusion: 86.25% / [[308, 46], [64, 382]], * Val accuracy / confusion: 67.88% / [[130, 100], [67, 223]] ------------------------------ Epoch 359 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.245095 - Iter 024 / 025, Loss: 0.152552 * Train accuracy / confusion: 86.38% / [[307, 51], [58, 384]], * Val accuracy / confusion: 66.54% / [[128, 102], [72, 218]] ------------------------------ Epoch 360 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.389888 - Iter 024 / 025, Loss: 0.382531 * Train accuracy / confusion: 86.62% / [[305, 50], [57, 388]], * Val accuracy / confusion: 65.96% / [[140, 90], [87, 203]] ------------------------------ Epoch 361 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.325952 - Iter 024 / 025, Loss: 0.448484 * Train accuracy / confusion: 85.62% / [[300, 54], [61, 385]], * Val accuracy / confusion: 65.77% / [[134, 96], [82, 208]] ------------------------------ Epoch 362 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.377690 - Iter 024 / 025, Loss: 0.215452 * Train accuracy / confusion: 86.12% / [[300, 59], [52, 389]], * Val accuracy / confusion: 67.50% / [[130, 100], [69, 221]] ------------------------------ Epoch 363 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.235124 - Iter 024 / 025, Loss: 0.305151 * Train accuracy / confusion: 87.75% / [[309, 47], [51, 393]], * Val accuracy / confusion: 66.35% / [[136, 94], [81, 209]] ------------------------------ Epoch 364 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.373561 - Iter 024 / 025, Loss: 0.249510 * Train accuracy / confusion: 86.38% / [[306, 50], [59, 385]], * Val accuracy / confusion: 67.69% / [[141, 89], [79, 211]] ------------------------------ Epoch 365 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.327573 - Iter 024 / 025, Loss: 0.369097 * Train accuracy / confusion: 86.62% / [[302, 51], [56, 391]], * Val accuracy / confusion: 63.65% / [[122, 108], [81, 209]] ------------------------------ Epoch 366 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.264933 - Iter 024 / 025, Loss: 0.196827 * Train accuracy / confusion: 85.38% / [[306, 54], [63, 377]], * Val accuracy / confusion: 69.23% / [[133, 97], [63, 227]] ------------------------------ Epoch 367 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.365813 - Iter 024 / 025, Loss: 0.262945 * Train accuracy / confusion: 86.12% / [[300, 57], [54, 389]], * Val accuracy / confusion: 66.92% / [[130, 100], [72, 218]] ------------------------------ Epoch 368 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.292628 - Iter 024 / 025, Loss: 0.203877 * Train accuracy / confusion: 87.38% / [[309, 45], [56, 390]], * Val accuracy / confusion: 65.96% / [[126, 104], [73, 217]] ------------------------------ Epoch 369 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.330568 - Iter 024 / 025, Loss: 0.314301 * Train accuracy / confusion: 86.00% / [[299, 56], [56, 389]], * Val accuracy / confusion: 69.23% / [[140, 90], [70, 220]] ------------------------------ Epoch 370 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.318975 - Iter 024 / 025, Loss: 0.430699 * Train accuracy / confusion: 88.25% / [[307, 50], [44, 399]], * Val accuracy / confusion: 67.12% / [[147, 83], [88, 202]] ------------------------------ Epoch 371 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.261468 - Iter 024 / 025, Loss: 0.204947 * Train accuracy / confusion: 86.00% / [[306, 46], [66, 382]], * Val accuracy / confusion: 65.96% / [[151, 79], [98, 192]] ------------------------------ Epoch 372 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.330037 - Iter 024 / 025, Loss: 0.284106 * Train accuracy / confusion: 86.75% / [[309, 51], [55, 385]], * Val accuracy / confusion: 65.77% / [[133, 97], [81, 209]] ------------------------------ Epoch 373 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.359935 - Iter 024 / 025, Loss: 0.321275 * Train accuracy / confusion: 85.38% / [[300, 54], [63, 383]], * Val accuracy / confusion: 67.31% / [[141, 89], [81, 209]] ------------------------------ Epoch 374 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.261681 - Iter 024 / 025, Loss: 0.252186 * Train accuracy / confusion: 87.12% / [[305, 49], [54, 392]], * Val accuracy / confusion: 68.46% / [[140, 90], [74, 216]] ------------------------------ Epoch 375 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.162714 - Iter 024 / 025, Loss: 0.353055 * Train accuracy / confusion: 87.25% / [[304, 50], [52, 394]], * Val accuracy / confusion: 69.42% / [[146, 84], [75, 215]] ------------------------------ Epoch 376 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.184417 - Iter 024 / 025, Loss: 0.226058 * Train accuracy / confusion: 86.88% / [[312, 43], [62, 383]], * Val accuracy / confusion: 68.65% / [[141, 89], [74, 216]] ------------------------------ Epoch 377 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.216011 - Iter 024 / 025, Loss: 0.325968 * Train accuracy / confusion: 86.38% / [[294, 58], [51, 397]], * Val accuracy / confusion: 69.42% / [[143, 87], [72, 218]] ------------------------------ Epoch 378 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.278223 - Iter 024 / 025, Loss: 0.356060 * Train accuracy / confusion: 87.00% / [[303, 50], [54, 393]], * Val accuracy / confusion: 69.04% / [[151, 79], [82, 208]] ------------------------------ Epoch 379 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.183529 - Iter 024 / 025, Loss: 0.312606 * Train accuracy / confusion: 87.38% / [[310, 48], [53, 389]], * Val accuracy / confusion: 69.04% / [[141, 89], [72, 218]] ------------------------------ Epoch 380 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.272392 - Iter 024 / 025, Loss: 0.204528 * Train accuracy / confusion: 85.88% / [[303, 54], [59, 384]], * Val accuracy / confusion: 68.08% / [[144, 86], [80, 210]] ------------------------------ Epoch 381 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.151763 - Iter 024 / 025, Loss: 0.506496 * Train accuracy / confusion: 86.25% / [[297, 53], [57, 393]], * Val accuracy / confusion: 65.96% / [[125, 105], [72, 218]] ------------------------------ Epoch 382 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.622965 - Iter 024 / 025, Loss: 0.464098 * Train accuracy / confusion: 86.75% / [[303, 54], [52, 391]], * Val accuracy / confusion: 66.73% / [[138, 92], [81, 209]] ------------------------------ Epoch 383 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.327215 - Iter 024 / 025, Loss: 0.283765 * Train accuracy / confusion: 88.50% / [[306, 48], [44, 402]], * Val accuracy / confusion: 66.92% / [[143, 87], [85, 205]] ------------------------------ Epoch 384 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.102482 - Iter 024 / 025, Loss: 0.266193 * Train accuracy / confusion: 88.25% / [[302, 48], [46, 404]], * Val accuracy / confusion: 67.69% / [[135, 95], [73, 217]] ------------------------------ Epoch 385 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.276481 - Iter 024 / 025, Loss: 0.199005 * Train accuracy / confusion: 87.62% / [[309, 44], [55, 392]], * Val accuracy / confusion: 68.65% / [[148, 82], [81, 209]] ------------------------------ Epoch 386 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.260999 - Iter 024 / 025, Loss: 0.200626 * Train accuracy / confusion: 89.00% / [[311, 38], [50, 401]], * Val accuracy / confusion: 67.12% / [[144, 86], [85, 205]] ------------------------------ Epoch 387 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.310869 - Iter 024 / 025, Loss: 0.278737 * Train accuracy / confusion: 86.62% / [[296, 60], [47, 397]], * Val accuracy / confusion: 68.27% / [[135, 95], [70, 220]] ------------------------------ Epoch 388 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.156018 - Iter 024 / 025, Loss: 0.362996 * Train accuracy / confusion: 87.12% / [[311, 45], [58, 386]], * Val accuracy / confusion: 65.38% / [[127, 103], [77, 213]] ------------------------------ Epoch 389 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.337791 - Iter 024 / 025, Loss: 0.346970 * Train accuracy / confusion: 88.38% / [[314, 47], [46, 393]], * Val accuracy / confusion: 67.50% / [[131, 99], [70, 220]] ------------------------------ Epoch 390 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.215683 - Iter 024 / 025, Loss: 0.416450 * Train accuracy / confusion: 86.88% / [[306, 52], [53, 389]], * Val accuracy / confusion: 68.46% / [[150, 80], [84, 206]] ------------------------------ Epoch 391 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.324091 - Iter 024 / 025, Loss: 0.513908 * Train accuracy / confusion: 86.38% / [[310, 49], [60, 381]], * Val accuracy / confusion: 69.42% / [[139, 91], [68, 222]] ------------------------------ Epoch 392 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.349839 - Iter 024 / 025, Loss: 0.279872 * Train accuracy / confusion: 86.75% / [[313, 44], [62, 381]], * Val accuracy / confusion: 65.19% / [[130, 100], [81, 209]] ------------------------------ Epoch 393 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.354579 - Iter 024 / 025, Loss: 0.323796 * Train accuracy / confusion: 86.75% / [[303, 51], [55, 391]], * Val accuracy / confusion: 67.69% / [[132, 98], [70, 220]] ------------------------------ Epoch 394 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.278391 - Iter 024 / 025, Loss: 0.270729 * Train accuracy / confusion: 86.25% / [[301, 53], [57, 389]], * Val accuracy / confusion: 69.62% / [[151, 79], [79, 211]] ------------------------------ Epoch 395 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.373721 - Iter 024 / 025, Loss: 0.193523 * Train accuracy / confusion: 87.25% / [[308, 53], [49, 390]], * Val accuracy / confusion: 66.35% / [[133, 97], [78, 212]] ------------------------------ Epoch 396 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.399159 - Iter 024 / 025, Loss: 0.176796 * Train accuracy / confusion: 86.62% / [[310, 47], [60, 383]], * Val accuracy / confusion: 67.12% / [[123, 107], [64, 226]] ------------------------------ Epoch 397 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.391268 - Iter 024 / 025, Loss: 0.126197 * Train accuracy / confusion: 87.62% / [[315, 43], [56, 386]], * Val accuracy / confusion: 71.15% / [[147, 83], [67, 223]] ------------------------------ Epoch 398 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.184456 - Iter 024 / 025, Loss: 0.288994 * Train accuracy / confusion: 86.38% / [[303, 54], [55, 388]], * Val accuracy / confusion: 69.04% / [[139, 91], [70, 220]] ------------------------------ Epoch 399 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.322689 - Iter 024 / 025, Loss: 0.343564 * Train accuracy / confusion: 85.75% / [[295, 60], [54, 391]], * Val accuracy / confusion: 69.42% / [[135, 95], [64, 226]] ------------------------------ Epoch 400 / 500, Learning rate: 1.00e-04 ------------------------------ - Iter 012 / 025, Loss: 0.224981 - Iter 024 / 025, Loss: 0.247337 * Train accuracy / confusion: 87.25% / [[303, 52], [50, 395]], * Val accuracy / confusion: 65.00% / [[138, 92], [90, 200]] ------------------------------ Epoch 401 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.197149 - Iter 024 / 025, Loss: 0.266154 * Train accuracy / confusion: 87.75% / [[309, 48], [50, 393]], * Val accuracy / confusion: 67.31% / [[135, 95], [75, 215]] ------------------------------ Epoch 402 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.192908 - Iter 024 / 025, Loss: 0.552034 * Train accuracy / confusion: 85.88% / [[297, 56], [57, 390]], * Val accuracy / confusion: 68.46% / [[142, 88], [76, 214]] ------------------------------ Epoch 403 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.248696 - Iter 024 / 025, Loss: 0.382873 * Train accuracy / confusion: 86.62% / [[305, 56], [51, 388]], * Val accuracy / confusion: 69.04% / [[139, 91], [70, 220]] ------------------------------ Epoch 404 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.326310 - Iter 024 / 025, Loss: 0.187402 * Train accuracy / confusion: 88.38% / [[308, 49], [44, 399]], * Val accuracy / confusion: 68.65% / [[137, 93], [70, 220]] ------------------------------ Epoch 405 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.532368 - Iter 024 / 025, Loss: 0.320579 * Train accuracy / confusion: 86.00% / [[298, 54], [58, 390]], * Val accuracy / confusion: 67.69% / [[137, 93], [75, 215]] ------------------------------ Epoch 406 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.259723 - Iter 024 / 025, Loss: 0.163980 * Train accuracy / confusion: 87.50% / [[304, 51], [49, 396]], * Val accuracy / confusion: 68.27% / [[138, 92], [73, 217]] ------------------------------ Epoch 407 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.329081 - Iter 024 / 025, Loss: 0.347353 * Train accuracy / confusion: 87.25% / [[303, 51], [51, 395]], * Val accuracy / confusion: 69.23% / [[141, 89], [71, 219]] ------------------------------ Epoch 408 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.262429 - Iter 024 / 025, Loss: 0.465179 * Train accuracy / confusion: 87.25% / [[308, 48], [54, 390]], * Val accuracy / confusion: 67.12% / [[134, 96], [75, 215]] ------------------------------ Epoch 409 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.381765 - Iter 024 / 025, Loss: 0.218449 * Train accuracy / confusion: 87.25% / [[308, 51], [51, 390]], * Val accuracy / confusion: 67.69% / [[138, 92], [76, 214]] ------------------------------ Epoch 410 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.224444 - Iter 024 / 025, Loss: 0.402838 * Train accuracy / confusion: 88.00% / [[308, 44], [52, 396]], * Val accuracy / confusion: 66.92% / [[130, 100], [72, 218]] ------------------------------ Epoch 411 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.182652 - Iter 024 / 025, Loss: 0.239858 * Train accuracy / confusion: 89.00% / [[306, 51], [37, 406]], * Val accuracy / confusion: 67.88% / [[132, 98], [69, 221]] ------------------------------ Epoch 412 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.183722 - Iter 024 / 025, Loss: 0.352489 * Train accuracy / confusion: 88.38% / [[307, 46], [47, 400]], * Val accuracy / confusion: 69.04% / [[142, 88], [73, 217]] ------------------------------ Epoch 413 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.313863 - Iter 024 / 025, Loss: 0.247466 * Train accuracy / confusion: 86.38% / [[313, 47], [62, 378]], * Val accuracy / confusion: 69.23% / [[135, 95], [65, 225]] ------------------------------ Epoch 414 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.287234 - Iter 024 / 025, Loss: 0.159500 * Train accuracy / confusion: 87.38% / [[311, 50], [51, 388]], * Val accuracy / confusion: 70.96% / [[141, 89], [62, 228]] ------------------------------ Epoch 415 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.274193 - Iter 024 / 025, Loss: 0.163884 * Train accuracy / confusion: 90.00% / [[313, 44], [36, 407]], * Val accuracy / confusion: 68.08% / [[139, 91], [75, 215]] ------------------------------ Epoch 416 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.319010 - Iter 024 / 025, Loss: 0.209079 * Train accuracy / confusion: 87.25% / [[308, 51], [51, 390]], * Val accuracy / confusion: 70.00% / [[144, 86], [70, 220]] ------------------------------ Epoch 417 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.354115 - Iter 024 / 025, Loss: 0.291146 * Train accuracy / confusion: 88.38% / [[313, 43], [50, 394]], * Val accuracy / confusion: 69.04% / [[145, 85], [76, 214]] ------------------------------ Epoch 418 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.159144 - Iter 024 / 025, Loss: 0.122425 * Train accuracy / confusion: 90.38% / [[310, 40], [37, 413]], * Val accuracy / confusion: 68.85% / [[135, 95], [67, 223]] ------------------------------ Epoch 419 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.313231 - Iter 024 / 025, Loss: 0.275626 * Train accuracy / confusion: 89.00% / [[314, 41], [47, 398]], * Val accuracy / confusion: 68.85% / [[139, 91], [71, 219]] ------------------------------ Epoch 420 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.464337 - Iter 024 / 025, Loss: 0.293620 * Train accuracy / confusion: 87.88% / [[313, 45], [52, 390]], * Val accuracy / confusion: 70.19% / [[143, 87], [68, 222]] ------------------------------ Epoch 421 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.255622 - Iter 024 / 025, Loss: 0.157391 * Train accuracy / confusion: 88.62% / [[312, 43], [48, 397]], * Val accuracy / confusion: 67.88% / [[146, 84], [83, 207]] ------------------------------ Epoch 422 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.183036 - Iter 024 / 025, Loss: 0.277365 * Train accuracy / confusion: 89.12% / [[318, 40], [47, 395]], * Val accuracy / confusion: 67.88% / [[142, 88], [79, 211]] ------------------------------ Epoch 423 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.249140 - Iter 024 / 025, Loss: 0.282926 * Train accuracy / confusion: 88.25% / [[316, 44], [50, 390]], * Val accuracy / confusion: 70.00% / [[143, 87], [69, 221]] ------------------------------ Epoch 424 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.182423 - Iter 024 / 025, Loss: 0.339314 * Train accuracy / confusion: 88.38% / [[317, 35], [58, 390]], * Val accuracy / confusion: 70.96% / [[154, 76], [75, 215]] ------------------------------ Epoch 425 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.140035 - Iter 024 / 025, Loss: 0.249136 * Train accuracy / confusion: 88.75% / [[310, 42], [48, 400]], * Val accuracy / confusion: 66.92% / [[140, 90], [82, 208]] ------------------------------ Epoch 426 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.266979 - Iter 024 / 025, Loss: 0.269331 * Train accuracy / confusion: 85.88% / [[302, 55], [58, 385]], * Val accuracy / confusion: 70.77% / [[144, 86], [66, 224]] ------------------------------ Epoch 427 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.160272 - Iter 024 / 025, Loss: 0.301172 * Train accuracy / confusion: 88.75% / [[314, 40], [50, 396]], * Val accuracy / confusion: 67.69% / [[138, 92], [76, 214]] ------------------------------ Epoch 428 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.427192 - Iter 024 / 025, Loss: 0.302517 * Train accuracy / confusion: 88.00% / [[314, 44], [52, 390]], * Val accuracy / confusion: 68.46% / [[129, 101], [63, 227]] ------------------------------ Epoch 429 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.226126 - Iter 024 / 025, Loss: 0.216013 * Train accuracy / confusion: 88.62% / [[321, 36], [55, 388]], * Val accuracy / confusion: 65.77% / [[133, 97], [81, 209]] ------------------------------ Epoch 430 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.147657 - Iter 024 / 025, Loss: 0.200949 * Train accuracy / confusion: 89.25% / [[309, 45], [41, 405]], * Val accuracy / confusion: 68.65% / [[146, 84], [79, 211]] ------------------------------ Epoch 431 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.334093 - Iter 024 / 025, Loss: 0.330246 * Train accuracy / confusion: 89.00% / [[314, 42], [46, 398]], * Val accuracy / confusion: 68.65% / [[138, 92], [71, 219]] ------------------------------ Epoch 432 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.273996 - Iter 024 / 025, Loss: 0.371192 * Train accuracy / confusion: 87.00% / [[309, 49], [55, 387]], * Val accuracy / confusion: 67.31% / [[137, 93], [77, 213]] ------------------------------ Epoch 433 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.326968 - Iter 024 / 025, Loss: 0.267718 * Train accuracy / confusion: 88.00% / [[308, 47], [49, 396]], * Val accuracy / confusion: 65.77% / [[129, 101], [77, 213]] ------------------------------ Epoch 434 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.239630 - Iter 024 / 025, Loss: 0.295502 * Train accuracy / confusion: 85.75% / [[304, 51], [63, 382]], * Val accuracy / confusion: 69.04% / [[143, 87], [74, 216]] ------------------------------ Epoch 435 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.285031 - Iter 024 / 025, Loss: 0.225735 * Train accuracy / confusion: 89.38% / [[313, 43], [42, 402]], * Val accuracy / confusion: 70.58% / [[140, 90], [63, 227]] ------------------------------ Epoch 436 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.365094 - Iter 024 / 025, Loss: 0.275692 * Train accuracy / confusion: 88.25% / [[313, 45], [49, 393]], * Val accuracy / confusion: 66.54% / [[132, 98], [76, 214]] ------------------------------ Epoch 437 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.418119 - Iter 024 / 025, Loss: 0.373097 * Train accuracy / confusion: 85.50% / [[293, 57], [59, 391]], * Val accuracy / confusion: 72.12% / [[148, 82], [63, 227]] ------------------------------ Epoch 438 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.272587 - Iter 024 / 025, Loss: 0.235693 * Train accuracy / confusion: 87.12% / [[309, 45], [58, 388]], * Val accuracy / confusion: 65.38% / [[135, 95], [85, 205]] ------------------------------ Epoch 439 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.348668 - Iter 024 / 025, Loss: 0.257017 * Train accuracy / confusion: 88.50% / [[309, 47], [45, 399]], * Val accuracy / confusion: 68.65% / [[143, 87], [76, 214]] ------------------------------ Epoch 440 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.318528 - Iter 024 / 025, Loss: 0.108455 * Train accuracy / confusion: 87.50% / [[311, 47], [53, 389]], * Val accuracy / confusion: 67.69% / [[136, 94], [74, 216]] ------------------------------ Epoch 441 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.357588 - Iter 024 / 025, Loss: 0.454980 * Train accuracy / confusion: 88.38% / [[312, 47], [46, 395]], * Val accuracy / confusion: 68.46% / [[131, 99], [65, 225]] ------------------------------ Epoch 442 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.391534 - Iter 024 / 025, Loss: 0.426754 * Train accuracy / confusion: 88.12% / [[308, 51], [44, 397]], * Val accuracy / confusion: 68.65% / [[138, 92], [71, 219]] ------------------------------ Epoch 443 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.496780 - Iter 024 / 025, Loss: 0.192025 * Train accuracy / confusion: 88.38% / [[312, 39], [54, 395]], * Val accuracy / confusion: 68.27% / [[145, 85], [80, 210]] ------------------------------ Epoch 444 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.333096 - Iter 024 / 025, Loss: 0.232313 * Train accuracy / confusion: 88.38% / [[310, 47], [46, 397]], * Val accuracy / confusion: 66.73% / [[127, 103], [70, 220]] ------------------------------ Epoch 445 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.340162 - Iter 024 / 025, Loss: 0.274075 * Train accuracy / confusion: 87.25% / [[308, 43], [59, 390]], * Val accuracy / confusion: 67.69% / [[134, 96], [72, 218]] ------------------------------ Epoch 446 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.201679 - Iter 024 / 025, Loss: 0.191799 * Train accuracy / confusion: 87.75% / [[308, 48], [50, 394]], * Val accuracy / confusion: 68.46% / [[133, 97], [67, 223]] ------------------------------ Epoch 447 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.289329 - Iter 024 / 025, Loss: 0.256989 * Train accuracy / confusion: 88.38% / [[317, 45], [48, 390]], * Val accuracy / confusion: 68.27% / [[145, 85], [80, 210]] ------------------------------ Epoch 448 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.216364 - Iter 024 / 025, Loss: 0.217649 * Train accuracy / confusion: 88.25% / [[311, 46], [48, 395]], * Val accuracy / confusion: 68.46% / [[136, 94], [70, 220]] ------------------------------ Epoch 449 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.152617 - Iter 024 / 025, Loss: 0.485991 * Train accuracy / confusion: 87.88% / [[313, 46], [51, 390]], * Val accuracy / confusion: 67.69% / [[132, 98], [70, 220]] ------------------------------ Epoch 450 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.197146 - Iter 024 / 025, Loss: 0.221006 * Train accuracy / confusion: 89.62% / [[318, 37], [46, 399]], * Val accuracy / confusion: 67.31% / [[138, 92], [78, 212]] ------------------------------ Epoch 451 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.326648 - Iter 024 / 025, Loss: 0.191547 * Train accuracy / confusion: 89.25% / [[313, 39], [47, 401]], * Val accuracy / confusion: 68.65% / [[138, 92], [71, 219]] ------------------------------ Epoch 452 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.252020 - Iter 024 / 025, Loss: 0.184670 * Train accuracy / confusion: 87.75% / [[310, 48], [50, 392]], * Val accuracy / confusion: 70.00% / [[151, 79], [77, 213]] ------------------------------ Epoch 453 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.209406 - Iter 024 / 025, Loss: 0.243506 * Train accuracy / confusion: 90.75% / [[325, 37], [37, 401]], * Val accuracy / confusion: 69.04% / [[129, 101], [60, 230]] ------------------------------ Epoch 454 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.335709 - Iter 024 / 025, Loss: 0.241283 * Train accuracy / confusion: 87.75% / [[304, 48], [50, 398]], * Val accuracy / confusion: 66.15% / [[131, 99], [77, 213]] ------------------------------ Epoch 455 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.396021 - Iter 024 / 025, Loss: 0.227048 * Train accuracy / confusion: 86.88% / [[304, 52], [53, 391]], * Val accuracy / confusion: 70.19% / [[148, 82], [73, 217]] ------------------------------ Epoch 456 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.297819 - Iter 024 / 025, Loss: 0.269234 * Train accuracy / confusion: 87.50% / [[306, 47], [53, 394]], * Val accuracy / confusion: 67.69% / [[134, 96], [72, 218]] ------------------------------ Epoch 457 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.364507 - Iter 024 / 025, Loss: 0.232785 * Train accuracy / confusion: 88.12% / [[313, 41], [54, 392]], * Val accuracy / confusion: 68.27% / [[139, 91], [74, 216]] ------------------------------ Epoch 458 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.378837 - Iter 024 / 025, Loss: 0.401717 * Train accuracy / confusion: 86.88% / [[304, 48], [57, 391]], * Val accuracy / confusion: 66.92% / [[142, 88], [84, 206]] ------------------------------ Epoch 459 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.235365 - Iter 024 / 025, Loss: 0.452045 * Train accuracy / confusion: 87.25% / [[304, 51], [51, 394]], * Val accuracy / confusion: 69.23% / [[137, 93], [67, 223]] ------------------------------ Epoch 460 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.218988 - Iter 024 / 025, Loss: 0.186786 * Train accuracy / confusion: 86.88% / [[308, 47], [58, 387]], * Val accuracy / confusion: 65.38% / [[120, 110], [70, 220]] ------------------------------ Epoch 461 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.289146 - Iter 024 / 025, Loss: 0.227319 * Train accuracy / confusion: 89.25% / [[314, 44], [42, 400]], * Val accuracy / confusion: 66.73% / [[136, 94], [79, 211]] ------------------------------ Epoch 462 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.550295 - Iter 024 / 025, Loss: 0.557715 * Train accuracy / confusion: 87.00% / [[311, 44], [60, 385]], * Val accuracy / confusion: 66.92% / [[138, 92], [80, 210]] ------------------------------ Epoch 463 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.226315 - Iter 024 / 025, Loss: 0.243557 * Train accuracy / confusion: 88.75% / [[310, 47], [43, 400]], * Val accuracy / confusion: 68.46% / [[136, 94], [70, 220]] ------------------------------ Epoch 464 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.200133 - Iter 024 / 025, Loss: 0.245728 * Train accuracy / confusion: 88.88% / [[308, 46], [43, 403]], * Val accuracy / confusion: 68.65% / [[137, 93], [70, 220]] ------------------------------ Epoch 465 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.383370 - Iter 024 / 025, Loss: 0.342114 * Train accuracy / confusion: 85.38% / [[292, 62], [55, 391]], * Val accuracy / confusion: 67.69% / [[131, 99], [69, 221]] ------------------------------ Epoch 466 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.275407 - Iter 024 / 025, Loss: 0.248409 * Train accuracy / confusion: 88.62% / [[312, 44], [47, 397]], * Val accuracy / confusion: 69.62% / [[139, 91], [67, 223]] ------------------------------ Epoch 467 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.160711 - Iter 024 / 025, Loss: 0.262883 * Train accuracy / confusion: 89.12% / [[313, 41], [46, 400]], * Val accuracy / confusion: 67.50% / [[129, 101], [68, 222]] ------------------------------ Epoch 468 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.335030 - Iter 024 / 025, Loss: 0.213714 * Train accuracy / confusion: 89.50% / [[317, 38], [46, 399]], * Val accuracy / confusion: 68.65% / [[141, 89], [74, 216]] ------------------------------ Epoch 469 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.313367 - Iter 024 / 025, Loss: 0.179520 * Train accuracy / confusion: 88.75% / [[314, 43], [47, 396]], * Val accuracy / confusion: 67.12% / [[141, 89], [82, 208]] ------------------------------ Epoch 470 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.293966 - Iter 024 / 025, Loss: 0.227349 * Train accuracy / confusion: 88.62% / [[309, 44], [47, 400]], * Val accuracy / confusion: 68.85% / [[151, 79], [83, 207]] ------------------------------ Epoch 471 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.206478 - Iter 024 / 025, Loss: 0.272488 * Train accuracy / confusion: 86.00% / [[312, 44], [68, 376]], * Val accuracy / confusion: 68.46% / [[142, 88], [76, 214]] ------------------------------ Epoch 472 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.329477 - Iter 024 / 025, Loss: 0.285011 * Train accuracy / confusion: 89.62% / [[324, 34], [49, 393]], * Val accuracy / confusion: 65.96% / [[129, 101], [76, 214]] ------------------------------ Epoch 473 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.208551 - Iter 024 / 025, Loss: 0.297275 * Train accuracy / confusion: 89.50% / [[315, 40], [44, 401]], * Val accuracy / confusion: 64.42% / [[130, 100], [85, 205]] ------------------------------ Epoch 474 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.255747 - Iter 024 / 025, Loss: 0.353866 * Train accuracy / confusion: 88.88% / [[316, 38], [51, 395]], * Val accuracy / confusion: 65.96% / [[130, 100], [77, 213]] ------------------------------ Epoch 475 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.245606 - Iter 024 / 025, Loss: 0.138523 * Train accuracy / confusion: 89.50% / [[315, 37], [47, 401]], * Val accuracy / confusion: 71.35% / [[140, 90], [59, 231]] ------------------------------ Epoch 476 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.201503 - Iter 024 / 025, Loss: 0.290780 * Train accuracy / confusion: 87.38% / [[306, 47], [54, 393]], * Val accuracy / confusion: 65.19% / [[122, 108], [73, 217]] ------------------------------ Epoch 477 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.582145 - Iter 024 / 025, Loss: 0.193031 * Train accuracy / confusion: 88.75% / [[313, 43], [47, 397]], * Val accuracy / confusion: 66.92% / [[132, 98], [74, 216]] ------------------------------ Epoch 478 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.276497 - Iter 024 / 025, Loss: 0.294208 * Train accuracy / confusion: 88.00% / [[311, 44], [52, 393]], * Val accuracy / confusion: 69.42% / [[138, 92], [67, 223]] ------------------------------ Epoch 479 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.103930 - Iter 024 / 025, Loss: 0.227435 * Train accuracy / confusion: 88.75% / [[315, 41], [49, 395]], * Val accuracy / confusion: 70.38% / [[146, 84], [70, 220]] ------------------------------ Epoch 480 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.413579 - Iter 024 / 025, Loss: 0.317463 * Train accuracy / confusion: 88.25% / [[317, 43], [51, 389]], * Val accuracy / confusion: 67.69% / [[130, 100], [68, 222]] ------------------------------ Epoch 481 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.345540 - Iter 024 / 025, Loss: 0.187874 * Train accuracy / confusion: 89.12% / [[315, 43], [44, 398]], * Val accuracy / confusion: 69.81% / [[140, 90], [67, 223]] ------------------------------ Epoch 482 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.234121 - Iter 024 / 025, Loss: 0.246196 * Train accuracy / confusion: 88.00% / [[310, 46], [50, 394]], * Val accuracy / confusion: 65.58% / [[127, 103], [76, 214]] ------------------------------ Epoch 483 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.295352 - Iter 024 / 025, Loss: 0.238515 * Train accuracy / confusion: 89.00% / [[314, 39], [49, 398]], * Val accuracy / confusion: 66.35% / [[131, 99], [76, 214]] ------------------------------ Epoch 484 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.305134 - Iter 024 / 025, Loss: 0.160282 * Train accuracy / confusion: 87.75% / [[313, 44], [54, 389]], * Val accuracy / confusion: 68.08% / [[147, 83], [83, 207]] ------------------------------ Epoch 485 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.297741 - Iter 024 / 025, Loss: 0.254893 * Train accuracy / confusion: 86.00% / [[300, 53], [59, 388]], * Val accuracy / confusion: 66.35% / [[135, 95], [80, 210]] ------------------------------ Epoch 486 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.419021 - Iter 024 / 025, Loss: 0.224701 * Train accuracy / confusion: 87.50% / [[321, 39], [61, 379]], * Val accuracy / confusion: 68.65% / [[145, 85], [78, 212]] ------------------------------ Epoch 487 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.225124 - Iter 024 / 025, Loss: 0.251367 * Train accuracy / confusion: 87.75% / [[310, 49], [49, 392]], * Val accuracy / confusion: 68.27% / [[134, 96], [69, 221]] ------------------------------ Epoch 488 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.413456 - Iter 024 / 025, Loss: 0.252640 * Train accuracy / confusion: 86.75% / [[302, 54], [52, 392]], * Val accuracy / confusion: 67.12% / [[135, 95], [76, 214]] ------------------------------ Epoch 489 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.344358 - Iter 024 / 025, Loss: 0.235768 * Train accuracy / confusion: 87.38% / [[303, 50], [51, 396]], * Val accuracy / confusion: 65.77% / [[139, 91], [87, 203]] ------------------------------ Epoch 490 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.270470 - Iter 024 / 025, Loss: 0.263688 * Train accuracy / confusion: 87.25% / [[303, 50], [52, 395]], * Val accuracy / confusion: 68.08% / [[135, 95], [71, 219]] ------------------------------ Epoch 491 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.157332 - Iter 024 / 025, Loss: 0.173638 * Train accuracy / confusion: 89.38% / [[314, 42], [43, 401]], * Val accuracy / confusion: 69.42% / [[137, 93], [66, 224]] ------------------------------ Epoch 492 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.325583 - Iter 024 / 025, Loss: 0.286154 * Train accuracy / confusion: 89.00% / [[313, 43], [45, 399]], * Val accuracy / confusion: 68.27% / [[146, 84], [81, 209]] ------------------------------ Epoch 493 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.201219 - Iter 024 / 025, Loss: 0.391564 * Train accuracy / confusion: 88.38% / [[312, 46], [47, 395]], * Val accuracy / confusion: 64.04% / [[120, 110], [77, 213]] ------------------------------ Epoch 494 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.156421 - Iter 024 / 025, Loss: 0.164445 * Train accuracy / confusion: 89.62% / [[315, 38], [45, 402]], * Val accuracy / confusion: 66.92% / [[137, 93], [79, 211]] ------------------------------ Epoch 495 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.283171 - Iter 024 / 025, Loss: 0.243719 * Train accuracy / confusion: 87.25% / [[304, 51], [51, 394]], * Val accuracy / confusion: 67.12% / [[141, 89], [82, 208]] ------------------------------ Epoch 496 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.361315 - Iter 024 / 025, Loss: 0.256294 * Train accuracy / confusion: 89.75% / [[311, 41], [41, 407]], * Val accuracy / confusion: 66.35% / [[131, 99], [76, 214]] ------------------------------ Epoch 497 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.349089 - Iter 024 / 025, Loss: 0.561778 * Train accuracy / confusion: 87.50% / [[304, 56], [44, 396]], * Val accuracy / confusion: 67.50% / [[134, 96], [73, 217]] ------------------------------ Epoch 498 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.188405 - Iter 024 / 025, Loss: 0.401302 * Train accuracy / confusion: 89.88% / [[314, 44], [37, 405]], * Val accuracy / confusion: 69.62% / [[145, 85], [73, 217]] ------------------------------ Epoch 499 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.213073 - Iter 024 / 025, Loss: 0.414705 * Train accuracy / confusion: 88.88% / [[312, 44], [45, 399]], * Val accuracy / confusion: 65.77% / [[132, 98], [80, 210]] ------------------------------ Epoch 500 / 500, Learning rate: 1.00e-05 ------------------------------ - Iter 012 / 025, Loss: 0.434353 - Iter 024 / 025, Loss: 0.211290 * Train accuracy / confusion: 89.00% / [[317, 42], [46, 395]], * Val accuracy / confusion: 67.50% / [[134, 96], [73, 217]] **************************************** Training Ends ****************************************
- Test accuracy (last model): 72.72% - Confusion matrix (last model): [[ 924 486] [ 365 1345]]
- Test accuracy (best model): 71.12% - Confusion matrix (best model): [[ 903 507] [ 394 1316]]
# checkpoint save path
if save_checkpoint:
os.makedirs('checkpoint/', exist_ok=True)
today = datetime.date.today()
torch.save(best_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_best')
torch.save(last_model_state, f'checkpoint/{today.year % 100}{today.month:02d}{today.day}_{nb_fname}_TinyResNet_last')
print('- Debug table:')
pprint.pp(last_test_debug, indent=2, width=100)
- Debug table:
{ '00299': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '00671212_160819'},
'00854': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01138301_230114'},
'01026': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01225123_050815'},
'00176': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00602435_270217'},
'00591': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00896386_240914'},
'01069': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01243158_301115'},
'00811': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01116389_271118'},
'01235': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01336270_040717'},
'00835': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01134450_140519'},
'00516': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00823206_130514'},
'00719': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01006707_260319'},
'00495': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '00805584_090819'},
'00862': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01139924_300315'},
'00913': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '01151967_160414'},
'00097': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00372136_181214'},
'00122': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00416942_190516'},
'00439': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00760780_141118'},
'01378': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01432133_160519'},
'00705': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_270116'},
'00212': {'GT': 1, 'Acc': ' 86.67%', 'Pred': [4, 26], 'edfname': '00617893_231018'},
'01105': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01266696_110516'},
'00671': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00958455_200917'},
'00531': {'GT': 0, 'Acc': ' 93.33%', 'Pred': [28, 2], 'edfname': '00840844_250119'},
'00192': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '00608961_131118'},
'00643': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '00948785_120116'},
'01177': {'GT': 1, 'Acc': ' 13.33%', 'Pred': [26, 4], 'edfname': '01300390_251116'},
'01209': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01318352_281118'},
'00341': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695058_191017'},
'00357': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00707209_261219'},
'00527': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00840062_080519'},
'01307': {'GT': 0, 'Acc': ' 36.67%', 'Pred': [11, 19], 'edfname': '01376302_060718'},
'00058': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00285244_020414'},
'00124': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '00418981_060116'},
'00508': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '00817022_010415'},
'00021': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00141670_081217'},
'00408': {'GT': 0, 'Acc': ' 36.67%', 'Pred': [11, 19], 'edfname': '00740750_110315'},
'00385': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '00723232_270318'},
'01125': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01276737_300616'},
'01330': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01392885_240718'},
'00329': {'GT': 0, 'Acc': ' 20.00%', 'Pred': [6, 24], 'edfname': '00685248_150414'},
'00277': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '00657017_281218'},
'00900': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01147100'},
'00700': {'GT': 1, 'Acc': ' 30.00%', 'Pred': [21, 9], 'edfname': '00985401_011117'},
'00584': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '00891889_060717'},
'01066': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01242983_071215'},
'00938': {'GT': 0, 'Acc': ' 0.00%', 'Pred': [0, 30], 'edfname': '01161826_050916'},
'00881': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01141790_190214'},
'00096': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00369252_131216'},
'01165': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '01296533_281116'},
'00697': {'GT': 0, 'Acc': ' 6.67%', 'Pred': [2, 28], 'edfname': '00983533_290618'},
'00030': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00164098_230317'},
'01123': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '01276165_040117'},
'00982': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01200248_290120'},
'00917': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01154159_230414'},
'00255': {'GT': 1, 'Acc': ' 53.33%', 'Pred': [14, 16], 'edfname': '00645911_021115'},
'01039': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01235034_290120'},
'00961': {'GT': 1, 'Acc': ' 96.67%', 'Pred': [1, 29], 'edfname': '01182545_070316'},
'00338': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00692685_200919'},
'00346': {'GT': 1, 'Acc': ' 76.67%', 'Pred': [7, 23], 'edfname': '00698358_020916'},
'00793': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01086373_020615'},
'00704': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00986061_240215'},
'00125': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '00418981_090316'},
'00859': {'GT': 1, 'Acc': ' 40.00%', 'Pred': [18, 12], 'edfname': '01139924_060417'},
'00471': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '00784417_100315'},
'00498': {'GT': 1, 'Acc': ' 0.00%', 'Pred': [30, 0], 'edfname': '00809366_050116'},
'01239': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01338557_190717'},
'00481': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '00796686_020819'},
'00369': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '00715828_111016'},
'01281': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '01358607_280918'},
'01360': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01415643_150119'},
'01288': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01364379_260919'},
'00885': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01142810_180214'},
'00858': {'GT': 1, 'Acc': ' 83.33%', 'Pred': [5, 25], 'edfname': '01139894_140214'},
'01138': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01281605_070716'},
'00821': {'GT': 0, 'Acc': ' 30.00%', 'Pred': [9, 21], 'edfname': '01128393_300715'},
'00870': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '01139947_120214'},
'01215': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01321744_130417'},
'00587': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00894185_250817'},
'00464': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00779318_101117'},
'00923': {'GT': 0, 'Acc': ' 26.67%', 'Pred': [8, 22], 'edfname': '01155730_070514'},
'00815': {'GT': 0, 'Acc': ' 80.00%', 'Pred': [24, 6], 'edfname': '01125477_030918'},
'01287': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '01364379_230118'},
'01160': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '01295899_041016'},
'00104': {'GT': 1, 'Acc': ' 80.00%', 'Pred': [6, 24], 'edfname': '00395714_170915'},
'01353': {'GT': 1, 'Acc': ' 73.33%', 'Pred': [8, 22], 'edfname': '01410438_241218'},
'01267': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01351393_111119'},
'01156': {'GT': 1, 'Acc': ' 90.00%', 'Pred': [3, 27], 'edfname': '01293646_120719'},
'00504': {'GT': 0, 'Acc': ' 3.33%', 'Pred': [1, 29], 'edfname': '00813343_041218'},
'01045': {'GT': 0, 'Acc': ' 86.67%', 'Pred': [26, 4], 'edfname': '01235281_191015'},
'01337': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '01400560_160419'},
'00094': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00366974_061118'},
'00741': {'GT': 0, 'Acc': ' 56.67%', 'Pred': [17, 13], 'edfname': '01025734_280715'},
'00303': {'GT': 1, 'Acc': ' 3.33%', 'Pred': [29, 1], 'edfname': '00672867_031116'},
'00156': {'GT': 1, 'Acc': ' 93.33%', 'Pred': [2, 28], 'edfname': '00502785_041019'},
'00851': {'GT': 0, 'Acc': ' 16.67%', 'Pred': [5, 25], 'edfname': '01138297_230114'},
'00730': {'GT': 0, 'Acc': ' 90.00%', 'Pred': [27, 3], 'edfname': '01011922_270815'},
'00343': {'GT': 1, 'Acc': '100.00%', 'Pred': [0, 30], 'edfname': '00695272_100519'},
'00756': {'GT': 1, 'Acc': ' 56.67%', 'Pred': [13, 17], 'edfname': '01035162_180119'},
'01232': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01335435_121119'},
'01007': {'GT': 0, 'Acc': '100.00%', 'Pred': [30, 0], 'edfname': '01211467_070415'},
'01247': {'GT': 1, 'Acc': ' 63.33%', 'Pred': [11, 19], 'edfname': '01339759_310717'},
'00588': {'GT': 0, 'Acc': ' 96.67%', 'Pred': [29, 1], 'edfname': '00895530_090616'},
'00076': {'GT': 1, 'Acc': ' 6.67%', 'Pred': [28, 2], 'edfname': '00317645_311016'},
'00653': {'GT': 1, 'Acc': ' 43.33%', 'Pred': [17, 13], 'edfname': '00952170_060516'}}
signal_headers = ['Fp1-AVG', 'F3-AVG', 'C3-AVG', 'P3-AVG',
'O1-AVG', 'Fp2-AVG', 'F4-AVG', 'C4-AVG',
'P4-AVG', 'O2-AVG', 'F7-AVG', 'T3-AVG',
'T5-AVG', 'F8-AVG', 'T4-AVG', 'T6-AVG',
'FZ-AVG', 'CZ-AVG', 'PZ-AVG', 'EKG']
from scipy.ndimage.filters import gaussian_filter1d
def jitter(X, amount):
left = X[:, :, :-amount]
right = X[:, :, -amount:]
X = torch.cat([left, right], dim=2)
return X
def blur_signal(X, sigma=1):
X_np = X.cpu().clone().numpy()
X_np = gaussian_filter1d(X_np, sigma, axis=2)
X.copy_(torch.Tensor(X_np).type_as(X))
return X
def create_class_visualization(target_y, model, dtype, **kwargs):
"""
Generate an image to maximize the score of target_y under a pretrained model.
Inputs:
- target_y: Integer in the range [0, 1000) giving the index of the class
- model: A pretrained CNN that will be used to generate the image
- dtype: Torch datatype to use for computations
Keyword arguments:
- l2_reg: Strength of L2 regularization on the image
- learning_rate: How big of a step to take
- num_iterations: How many iterations to use
- blur_every: How often to blur the image as an implicit regularizer
- max_jitter: How much to gjitter the image as an implicit regularizer
- show_every: How often to show the intermediate result
"""
model.type(dtype)
l2_reg = kwargs.pop('l2_reg', 1e-3)
learning_rate = kwargs.pop('learning_rate', 25)
num_iterations = kwargs.pop('num_iterations', 15000)
blur_every = kwargs.pop('blur_every', 10)
max_jitter = kwargs.pop('max_jitter', 100)
show_every = kwargs.pop('show_every', 5000)
# Randomly initialize the image as a PyTorch Tensor, and make it requires gradient.
signal = torch.randn(2, *train_dataset[0]['signal'].shape).mul_(1.0).type(dtype).requires_grad_().to(device)
blur_signal(signal.data, sigma=3)
for t in tqdm(range(num_iterations)):
# Randomly jitter the image a bit; this gives slightly nicer results
jittering = random.randint(0, max_jitter)
signal.data.copy_(jitter(signal.data, jittering))
# run the model
age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
scores = model(signal, age)
# score loss and L-2 regularization
loss = scores[:, target_y] - l2_reg * torch.norm(signal)
loss = loss.sum()
# compute the gradients on the image
loss.backward()
with torch.no_grad():
# gradient ascent
signal += learning_rate * signal.grad
# manually zero the gradients after running the backward pass
signal.grad.zero_()
# Undo the random jitter
signal.data.copy_(jitter(signal.data, -jittering))
# As regularizer, periodically blur the image
if t % blur_every == 0:
blur_signal(signal.data, sigma=1)
# Periodically show the signal
if t == 0 or (t + 1) % show_every == 0 or t == num_iterations - 1:
fig = plt.figure(num=1, clear=True,
figsize=(15.0, 10.0), constrained_layout=True)
for s in range(signal.shape[0]):
ax = fig.add_subplot(signal.shape[0], 1, s + 1)
sig = signal[s].data.clone().cpu()
for (k, h) in enumerate(signal_headers):
ax.plot(np.arange(sig.shape[1]) / 200, sig[k], label=h)
class_name = class_label_to_type[target_y]
plt.legend(shadow=True).get_frame().set_facecolor('white')
plt.title('%s\nIteration %d / %d' % (class_name, t + 1, num_iterations))
plt.show()
fig.clear()
plt.close(fig)
return signal
#dtype = torch.FloatTensor
dtype = torch.cuda.FloatTensor # Uncomment this to use GPU
model.type(dtype)
target_y = 0 # Normal, NV-MCI, NV-Dementia
out = create_class_visualization(target_y, model, dtype)
age = torch.tensor([age_mean, age_mean], dtype=torch.float32).to(device)
scores = model(out, age)
pred = F.log_softmax(scores, dim=1)
estimation = pred.argmax(dim=-1)
print(scores)
print(pred)
print(estimation)
tensor([[ 758.0693, -851.5200],
[ 664.0812, -741.3008]], device='cuda:0', grad_fn=<AddmmBackward>)
tensor([[ 0.0000, -1609.5894],
[ 0.0000, -1405.3820]], device='cuda:0',
grad_fn=<LogSoftmaxBackward>)
tensor([0, 0], device='cuda:0')